282 results about "Thermodynamic model" patented technology

The invention provides an energy-saving temperature control optimization method and system based on a central air-conditioning simulation platform, and relates to the field of central air-conditioning simulation platforms, and the method comprises the steps: collecting the operation parameters of a central air-conditioning system in real time through an Internet of Things sensor network, constructing a multi-dimensional dynamic data set in combination with historical data and outdoor meteorological data, and carrying out the calculation of the multi-dimensional dynamic data set; a physical model and machine learning hybrid driven simulation engine is adopted, a dynamic thermodynamic model of the central air-conditioning system is established, and a multi-objective optimization function of a simulation platform model is defined according to user comfort requirements, energy consumption cost constraints and environmental policy indexes; and adopting a hybrid optimization strategy of fusion of reinforcement learning and a genetic algorithm, iteratively optimizing control parameters in the simulation platform model, deploying a digital twin system according to the energy-saving strategy set, predicting potential faults through a virtual sensor, correcting the parameters of the simulation platform model, and realizing closed-loop control and continuous optimization. The method is used for overcoming the defect that a closed-loop feedback mechanism is lacked in the prior art.

The invention relates to a ship safety monitoring method, system and device based on data fusion, and relates to the technical field of ship navigation safety, and the ship safety monitoring method comprises the steps: collecting multi-source heterogeneous data; preprocessing the multi-source heterogeneous data; carrying out fusion processing on the multi-source heterogeneous data based on an information entropy theory; a ship safety domain model is constructed, trajectory prediction is executed, a collision risk index is calculated, and the ship collision risk is evaluated; and performing anomaly detection on the ship equipment operation data based on manifold learning and a thermodynamic model. According to the invention, a multi-source heterogeneous data fusion technology is adopted, multi-dimensional data sources are integrated, and omnibearing ship safety situation awareness is constructed. The early warning time is prolonged to 8-10 minutes, which is far better than the early warning time of 3-5 minutes in the prior art. The system thoroughly solves the problem that subsystems in a traditional ship monitoring system operate independently and do not communicate with one another, the crew information acquisition cost is reduced, and the number of times of interactive operation is reduced by 42%.

The invention belongs to the field of equipment coupling monitoring, and particularly relates to a dynamic coupling compensation method for thermal expansion and axial displacement, which comprises the following steps of: calculating a first characteristic value for representing reference dynamic offset of a sensor based on a three-dimensional thermal-structure coupling model by acquiring a thermal expansion parameter and axial displacement parameter sequence of a casing; calculating a second characteristic value representing the real position change of the rotor in combination with a rotor-casing axial thermodynamic model, establishing a piecewise coupling function considering a nonlinear effect, working condition self-adaption and cross interference, and eliminating the mechanical thermal inertia and measurement system lag influence through a dynamic delay compensation mechanism; an accurate axial displacement measurement total error compensation index is generated, and grading compensation actions are intelligently triggered according to error grades; the problem of measurement distortion caused by dynamic coupling of thermal expansion and axial displacement is effectively solved, and the accuracy and reliability of state monitoring of the rotating machine are remarkably improved.

The invention relates to the technical field of temperature control, in particular to a mass concrete water cooling water temperature control method and system. The method comprises the following steps: collecting concrete key parameters through a multi-source sensor, constructing a microenvironment model based on information geometry, and generating a thermosensitive characteristic spectrum; forming a distributed thermodynamic model by utilizing a mutual information routing algorithm and heat-fluid-solid coupling analysis, and calculating an optimal cooling strategy; water flow path and flow optimization is realized in combination with fractional order particle swarm optimization; a pump set and a valve are adjusted through fuzzy self-adaptive control; and a potential instability region is identified through the spectrum energy gradient, and risk early warning is triggered. The precision and reliability of mass concrete cooling temperature control are remarkably improved, and intelligent, efficient and safe temperature control adjustment in the whole process is achieved.

The invention discloses a method and a system for monitoring the temperature of an energy storage battery in a high-altitude area. Through environment adaptive feature reconstruction, thermodynamic model correction and multi-frequency EIS fusion feature extraction are utilized to generate a feature vector adaptive to the plateau environment. The thermodynamic model correction adjusts the convective heat transfer coefficient by introducing an air pressure correction coefficient; the multi-frequency EIS fusion feature selects a specific frequency point impedance value to construct a vector, and the weight is dynamically adjusted through a random forest algorithm. The lightweight hybrid machine learning model integrates the advantages of LightGBM, 1D-CNN and a physical constraint particle filter model, and realizes accurate prediction for different working conditions. The plateau exclusive training mechanism covers data enhancement, transfer learning and online calibration, and the generalization ability and adaptability of the model are improved. According to the method, the problems of low temperature monitoring precision and poor model adaptability of the energy storage battery in the high-altitude area are solved, the monitoring precision and the system reliability are remarkably improved, and a guarantee is provided for safe and stable operation of a high-altitude energy storage system.

The invention relates to the technical field of equipment parameter optimization, and discloses a liquid cooling system parameter optimization method and system for a data center. The method comprises the steps of performing wavelet noise reduction processing on thermal load data of equipment, and constructing a time sequence heat generation model; the thermodynamic model and the time sequence heat generation model are fused to generate a comprehensive heat model, an objective function and constraint conditions are set, and a parameter combination is output; the parameter optimization model generates a standard parameter combination based on the parameter combination, the standard parameter combination is substituted into the parameter optimization model for evaluation, and an optimal parameter combination is output; the operation parameters of the liquid cooling system are adjusted in real time, the actual system operation data of the liquid cooling system are collected, the actual system operation data are compared with the expected equipment thermal load data of the data center, the parameter deviation is obtained, and the operation parameters are dynamically adjusted based on the parameter deviation. According to the invention, the efficiency and accuracy of parameter optimization of the liquid cooling system are improved.

The invention discloses a fuel cell vehicle thermal management system and a construction method thereof, and the fuel cell vehicle thermal management system comprises a thermodynamic modeling module, a double-layer fuzzy sliding mode controller, an actuator cooperative control module, a working condition adaptive module and a fault protection module. According to the thermal management system of the fuel cell vehicle and the construction method of the thermal management system, the dynamic thermodynamic model is established, and the double-layer fuzzy sliding mode controller and the actuator cooperative control module are designed, so that millisecond-level high-precision tracking of the temperature of the electric pile and online real-time compensation of unknown disturbance are realized; meanwhile, stable operation of the system in the whole working condition domain range can be ensured through the working condition self-adaption module and the fault protection module, and the system has the advantages of being high in control precision, high in anti-interference capacity and good in system reliability.

The invention relates to the technical field of gas turbine performance prediction, and provides a thermodynamics-based gas turbine performance lightweight modeling method, which comprises the following steps of: 1, acquiring actual operation data of a gas turbine, and preprocessing the operation data; 2, establishing a thermodynamic model of the gas turbine; 3, establishing a gas turbine agent model; and step 4, training the gas turbine proxy model to obtain a trained gas turbine proxy model. According to the method, the influence of external environment conditions and power requirements on working condition operation conditions can be eliminated, and key gas turbine performance parameters can be quickly obtained.

The invention discloses a universal nucleic acid probe design method based on hybridization thermodynamics and kinetics, which comprises the following steps: 1) determining a target amplification region according to a fragment interval, generating a primer pair which meets the length requirement and covers a target fragment, calculating the Gibbs free energy change of nucleic acid hybridization by adopting an intelligent nucleic acid hybridization algorithm, and calculating the Gibbs free energy change of the target fragment according to the Gibbs free energy change; by combining chemical thermodynamics, kinetic parameters, sequence complementarity and enzymatic reaction characteristics, generating an optimal primer pair under a multi-dimensional constraint condition; and 2) on the basis of the generated optimal primer pair, generating a probe combination meeting a free energy difference threshold as a candidate pool, screening the probe combination with the highest objective function value from the candidate pool through an iterative process, and updating the candidate pool step by step until the primer pair and the probe combination with the highest objective function value are output. By introducing an intelligent algorithm and combining a thermodynamic model, a dynamic model and specificity evaluation, an optimal primer and probe combination is automatically generated, and the stability and reliability of design are ensured.

The invention relates to the technical field of energy utilization, and discloses an urban heat and cold supply centralized energy comprehensive utilization method. The method comprises the following steps: S1, acquiring physical parameters and operation data of an urban heating and cooling system, wherein the physical parameters comprise a system initial temperature field, a thermal diffusion coefficient, heat source distribution, equipment performance parameters and heating and cooling demand loads; the invention further provides an urban heat and cold supply centralized energy comprehensive utilization system. The data acquisition module is used for acquiring physical parameters and operation data of the urban heating and cooling system; and the thermodynamic modeling module is used for constructing a thermodynamic model based on the law of conservation of energy. By constructing an optimization model based on energy conservation and entropy increase minimization, energy loss in a heating and cooling system is remarkably reduced, by optimizing energy distribution in real time and dynamically adjusting temperature field distribution, invalid energy consumption is reduced to the maximum extent, the overall energy utilization rate of the system is increased, and the energy utilization rate of the system is increased. And therefore, the heating and cooling system can operate efficiently under various working conditions.

The invention relates to the technical field of data analysis and visualization, in particular to a sales data sparsity compensation and self-adaptive visualization method and a sales data sparsity compensation and self-adaptive visualization system, a knowledge graph containing a sales node time sequence relation is constructed through spatio-temporal clustering and attribute division, a bidirectional time sequence processing mechanism is adopted, historical evolution and future trend are considered at the same time, and the sales data sparsity compensation and self-adaptive visualization method is established. Historical and future relation strength among nodes is obtained, sales association probability among the nodes is predicted, comprehensive mastering of node relations is realized, prediction accuracy is improved, a missing value regression model of a multi-dimensional relation is constructed on the basis of a graph attention mechanism, attributes and states needing to be filled are identified, and the probability of sales association between the nodes is predicted. Potential relation reasoning is carried out through Monte Carlo tree search, an adaptive node attribute filling result is obtained, a visual layout strategy is designed according to node weights and attribute values, a sales flow change trend is displayed through a thermodynamic model, space-time correlation characteristics of sales data are effectively captured, and a solid foundation is provided for sparsity compensation.

The invention relates to the technical field of air conditioner temperature adjustment, in particular to an energy-saving control method, device and equipment for machine room air conditioner group control, a storage medium and a computer program product. The method comprises the following steps: acquiring temperature and humidity data in a machine room, power consumption data of load equipment and operation parameters of air conditioning equipment; synchronizing the data according to timestamps to generate a corresponding multi-source feature data matrix; constructing spatial thermodynamic model parameters based on the multi-source feature data matrix; on the basis of the space thermodynamic model parameters, the temperature evolution trend in the target time domain is predicted, and a control instruction sequence of the air conditioning equipment is generated on the basis of a prediction result; and if the control instruction sequence meets the preset temperature range constraint, the preset temperature change rate constraint and the preset control time interval constraint, the corresponding control instruction is sent to the air conditioner equipment, and the air conditioner group control energy-saving efficiency is improved.

The invention discloses a new energy power generation prediction method based on weather data, and the method comprises the following steps: a, carrying out the characteristic analysis of a raw material, collecting the physical characteristic parameters of a biomass raw material, including the heat value of a dry basis, the moisture content of a wet basis and the mass, and generating an initial power generation prediction through a thermodynamic model; b, a distributed temperature and humidity sensor network is deployed in a raw material storage area, temperature, humidity and rainfall data are collected in real time, and the raw material mildew rate and moisture content change are dynamically predicted in combination with environmental parameters; through multi-dimensional data perception, multi-physical field coupling modeling and an intelligent decision engine, dynamic prediction of the raw material quality and the transportation efficiency in biomass energy power generation is realized, the power generation capacity prediction error is reduced, meanwhile, the raw material loss is reduced, and a key technical support is provided for large-scale efficient utilization of biomass energy power generation in new energy power generation.

The invention provides a cold heading steel wire rod rolling temperature closed-loop control method and system based on PID, and relates to the technical field of cold heading steel wire rod rolling process control, and the cold heading steel wire rod rolling temperature closed-loop control method comprises the following steps: determining temperature control parameters of a rolling area of a rolling mill in different rolling stages of a cold heading steel wire rod according to process requirements of the cold heading steel wire rod; constructing dynamic thermodynamic models of different rolling stages; the real-time state data and the real-time temperature data are preprocessed; the extracted temperature control parameters are compared with the preprocessed real-time temperature data; based on the dynamic thermodynamic model and the real-time temperature deviation, the control quantity is calculated through a PID algorithm, and a control instruction is output to an execution mechanism of the rolling mill; and an execution mechanism of the rolling mill receives the instruction and carries out temperature adjustment action. The method can effectively guarantee that the temperature in each rolling stage is stable, the quality consistency of cold heading steel wire rod products is improved, and the dynamic change requirement in the rolling process is met.

The invention provides a thermodynamic optimization method and device for a thermoelectric power generation module and a medium. Belongs to the field of thermoelectric power generation, and comprises the following steps: firstly, determining an optimization target to maximize power output or improve energy conversion efficiency, then establishing a thermodynamic model which comprises heat conduction, heat convection and thermoelectric conversion processes, and setting parameters. An improved ant colony algorithm is adopted, a self-adaptive optimization strategy capable of automatically adjusting and optimizing parameters is designed, and the algorithm introduces volatilization factors and adds random disturbance to optimize the search process. And finally, a multi-objective optimization algorithm is introduced to realize effective balance between the electric power and the thermoelectric conversion efficiency. Through the series of steps, the thermodynamic property of the thermoelectric power generation module can be effectively optimized, so that the power output and energy conversion efficiency of the thermoelectric power generation module are improved.

The invention relates to the technical field of oil and gas field development, and discloses a horizontal well multiphase flow profile inversion method based on multisource data fusion, which comprises the following steps: S1, laying optical fibers and acquiring data; s2, data preprocessing; s3, obtaining empirical parameters and a multi-source database; s4, judging a fluid scene and constructing a solver model; s5, iterative solution and phase fraction inversion are carried out, according to the empirical parameters and the multi-source database, the solver model constructed in the step S4 is adopted, solution is carried out in different phase number scenes, and an inversion index result is obtained; and S6, visual output and abnormal flow detection are carried out, and the inversion index result obtained in the step S5 is visually presented in the depth direction of the shaft and is used for assisting in judging abnormal phenomena. According to the method, the multiphase flow thermodynamic model is constructed based on the state equation, the water-liquid ratio and the gas-oil ratio are dynamically inverted through the iterative optimization algorithm in combination with the DAS sound velocity data, and high-precision characterization of multiphase flow characteristics is achieved.

The invention provides a ship propeller design optimization method and system based on machine learning, and relates to the technical field of ship propeller design, and the method comprises the steps: building a parameterized curved surface based on a geometric control point coordinate set, converting the parameterized curved surface into a signed distance field (SDF), extracting an SDF zero contour surface to generate an initial grid, and carrying out the gradient optimization of control points to meet the demolding angle constraint, calculating the local thickness of the blade based on the SDF, and predicting shrinkage cavity defect probability distribution by adopting a differentiable thermodynamic model and a spatial-temporal characteristic network; fusing the defect probability and the hydrodynamic performance to construct a target function, reversely propagating the gradient to a geometric control point through a thermal field, a grid and an SDF through differentiable simulation, and driving the gradient to synchronously update; and iteratively executing the process, terminating after the defect probability threshold, the performance tolerance and the convergence condition are met, and outputting the propeller geometric model with excellent hydrodynamic performance and high manufacturability.

The invention relates to the technical field of manufacturing of electrical element assemblies, and discloses a cold and heat exchange system of a liquid cooling cabinet and a use method of the cold and heat exchange system. The cold and heat exchange method of the liquid cooling cabinet comprises the steps that a complex thermodynamic model of the liquid cooling cabinet is processed through a hierarchical model distillation algorithm, and an ultra-lightweight thermodynamic digital twin model is obtained; processing the operation state of the liquid cooling cabinet through a multi-mode micro-sensor network to obtain a lightweight environment and load feature vector; processing the lightweight environment and load feature vector and the ultra-lightweight thermodynamic digital twin model through a micro predictive controller to obtain an adaptive liquid cooling control strategy; processing the self-adaptive liquid cooling control strategy through an ultra-low power consumption execution unit to obtain an accurately executed physical cooling effect; according to the invention, through an optimization algorithm, efficient control of the liquid cooling cabinet system is realized in a resource limited environment, the precision, the response speed and the energy efficiency are improved, the environmental adaptability and reliability are enhanced, and the bottleneck of a traditional system is broken through.

The invention relates to the technical field of air source heat pumps, in particular to a start-stop balancing method, device and equipment for a compressor unit and a storage medium. Acquiring an environment temperature and a user set temperature; generating a thermal load demand signal according to the environment temperature and the user set temperature; generating an operation signal based on a preset thermodynamic model and the thermal load demand signal; performing type analysis on the operation signal; when the type of the operation signal is a slow loading operation signal, the compressor unit is controlled to perform scheduling operation; the accumulated operation time of the compressor unit is obtained, and the start-stop state of the compressor unit is controlled according to the accumulated operation time; when the type of the operation signal is a full-load operation signal, the compressor unit is controlled to perform full-load operation; start and stop of the compressor are controlled through reasonable scheduling and time accumulation, long-term high-load operation is avoided, abrasion of key parts is reduced, the service life of equipment is prolonged, maintenance cost is reduced, and meanwhile operation efficiency and system stability are improved.

The invention discloses a temperature control equipment control method and system based on a light storage direct-flexible building, and the method comprises the steps: constructing a building thermodynamic model and a multi-objective optimization function according to environment data, and the static parameters and state data of the light storage direct-flexible building, and determining the temperature adjustment time of temperature control equipment according to the building thermodynamic model, and solving the multi-objective optimization function according to a preset constraint condition to obtain a temperature adjustment value of the temperature control equipment, and finally performing parameter adjustment on the temperature control equipment according to the temperature adjustment time and the temperature adjustment value. The limitation of traditional mechanical threshold value control is broken through, the intelligent level and the operation and maintenance efficiency of the light storage direct flexible building are improved, temperature regulation and control of the temperature control equipment are more accurate, and energy consumption is reduced.

The invention discloses a mass concrete temperature control construction method and system based on phase change energy storage, and the method comprises the steps: S100, building a BIM model for a concrete member pouring region according to a design size, setting a temperature sensor in a concrete member to monitor data in real time, and predicting a temperature field in combination with the BIM model; s200, the space between the conventional cooling water pipe and the concrete protection layer is filled with phase change microcapsules in a gradient density mode, a phase change energy storage buffer layer is formed, and transfer of heat to the interior of the concrete member is delayed; s300, according to the predicted temperature field, the water inlet flow and the water temperature are dynamically adjusted, the temperature peak is controlled, and the cooling rate is controlled; s400, fiber grating sensors are arranged at the four corners and the midspan of the concrete member, and the strain change rate is detected; and S500, establishing a digital twin temperature control platform, integrating temperature, humidity and strain data, constructing a three-dimensional thermodynamic model, predicting the temperature rise trend of the concrete member, and performing adaptive regulation and control on the temperature. Temperature difference inside and outside the concrete is controlled through phase change temperature control.

The invention relates to the technical field of air source heat pump unit control, and discloses a control method for an air source heat pump unit. The method comprises the following steps: acquiring environment temperature and humidity data in real time, and performing noise filtering and time synchronization; generating a temperature prediction sequence based on the sliding window and the LSTM model; fluctuation characteristics are extracted through an optimization algorithm, and compressor control signals are generated; estimating the thickness of a frost layer in combination with a thermodynamic model and dynamically generating a defrosting instruction; closed-loop control parameters are generated through normalization processing and weight distribution; and finally, a system execution command is generated through multi-objective optimization, and compressor regulation and control and system health monitoring are achieved. The unit operation efficiency can be improved, the energy consumption can be reduced, and the defrosting control accuracy and the system stability can be enhanced.

The invention provides an intelligent blower temperature and wind speed adaptive control method and system, and relates to the field of intelligent control, and the method comprises the steps: collecting temperature, humidity and wind speed, and constructing a local feature map based on feature vectors; a dynamic evaporation thermodynamic model is established according to the local feature map and used for calculating the evaporation rate of each area, and then the energy requirement for achieving the needed drying effect of each area is calculated according to the evaporation rate; a competitive sensing type wind energy mapping model is established to map energy requirements into control signals used for controlling air outlet parameters, namely wind cavity control signals, and regional self-adaptive adjustment of wind temperature and wind speed in space is achieved; actual air flow output collected in real time is compared with an air cavity control signal, and a feedback difference mechanism is constructed to conduct iterative correction on the dynamic evaporation thermodynamic model and the energy requirement; the physical state change in the hair drying process can be perceived in real time, and dynamic balance can be realized by integrating the use habit and comfort perception of the user.

The invention discloses a hydraulic compressed air energy storage system based on a gas storage salt cavern and an optimization design method. The optimization design method comprises the steps that initial parameters of the energy storage system are set; heat exchange between the wall surface of the salt cavern and fluid is considered, and an improved thermodynamic model is obtained through calculation; and calculating to obtain the optimal height-diameter ratio of the salt cavern based on the improved thermodynamic model by taking the maximum indicated cycle efficiency as an optimization target. According to the method, the height-diameter ratio of the salt cavern can be optimized, so that the electric cycle efficiency, the energy storage density and the operation income of the system are remarkably improved.

The invention relates to a lithium battery overheating runaway monitoring and disposing method, which comprises the following steps: S1, establishing a thermodynamic model of a lithium battery: establishing the thermodynamic model according to heat generation, heat conduction and heat convection in the battery, heat exchange between the battery and an external environment, and change of thermophysical parameters of a battery material along with temperature; s2, establishing an electrochemical model of the lithium battery: establishing the electrochemical model according to the material composition, the structural design and the working condition of the battery, the voltage, the current and the capacity of the battery in the charging and discharging process, and the influence of battery aging on the performance; s3, simulating the internal state of the battery: simulating the internal state of the battery in the charging and discharging process by combining the thermodynamic model and the electrochemical model; and S4, predicting the overheat runaway risk of the battery: establishing a prediction model of the overheat runaway risk of the battery based on the simulation result of S3, and evaluating the overheat runaway risk of the battery in real time through the prediction model.

The invention belongs to the technical field of automobile electronics, and particularly relates to a tire pressure monitoring dynamic calibration method and system fused with vehicle speed data, and the method comprises the steps: obtaining real-time tire pressure, tire temperature, vehicle speed and environment temperature; based on the vehicle speed, the environment temperature and the calibration parameters, the tire theoretical temperature is estimated through a dynamic thermodynamic model; the real-time tire temperature and the theoretical temperature are fused through Kalman filtering, and the corrected internal temperature is obtained; and according to the real-time tire pressure, the corrected internal temperature and the cold tire reference temperature, a cold tire pressure equivalent value is calculated to judge the tire pressure state. By the adoption of the technical scheme, the interpretation ambiguity of traditional tire pressure monitoring can be overcome, the cold tire pressure equivalent value with more guiding significance is provided, and the accuracy, robustness and self-adaptive learning capacity of the system are enhanced.

The invention provides a PI control method and device for laser soldering based on observation compensation, a controller and a program product, and the method comprises the steps: building a laser soldering thermodynamic model containing a thermal disturbance term based on a lumped parameter method, and constructing a state-space equation; designing a state observer based on the state-space equation, and estimating a state variable of the state-space equation and external disturbance acting on the state variable in real time; calculating a feedforward control quantity according to a target temperature curve and the thermodynamic model, calculating a compensation control quantity according to a disturbance value estimated by an observer, and calculating a PI control quantity according to the deviation between the output temperature and the target temperature to obtain a total control quantity; and in each sampling period, the total control quantity is dynamically adjusted according to the deviation between the current welding spot temperature and the target temperature, so that the temperature error tends to zero. According to the method, the disturbance observation technology and the feedforward-PI control are combined, and high-precision and high-robustness control over the welding temperature is achieved.

According to the intelligent plunger pump temperature control method and system based on model predictive control, a thermodynamic model predictive control algorithm is introduced, key parameters such as the oil temperature of a plunger pump body, the water temperature of a water tank and the environment temperature are brought into a unified calculation model, and cooperative closed-loop control over a heating plate, a semiconductor chilling plate and a circulating pump is achieved. By constructing the heat balance equation of the lumped heat capacity system and solving the rolling optimization problem in the limited time domain, the heat load change of the plunger pump can be accurately predicted and adjusted in advance, the oil temperature is always stabilized in the preset target interval, and the temperature control precision is remarkably improved; meanwhile, mutual exclusion constraints of heating and refrigerating power are set, and weights are dynamically adjusted and optimized according to working conditions, so that meaningless consumption of energy is effectively avoided, and the operation cost of equipment is reduced; in addition, according to the control method, preheating, cooling and energy-saving modes can be automatically recognized, so that the plunger pump is rapidly started in the severe cold environment and stably operates in the high-temperature environment.

The invention discloses a heating system feedforward control method integrating building thermal inertia and meteorological prediction, which comprises the following steps of: firstly, dynamically identifying building thermal parameters of each room so as to quantify the thermal inertia; then, inputting the parameters and future meteorological prediction data into a feedforward controller; and the controller predicts a room temperature change trend caused by future meteorological disturbance based on a thermodynamic model, calculates a required feedforward compensation control quantity, and adjusts a heating system in advance so as to counteract the disturbance. Through combination of dynamic identification and predictive control, heating control is changed into active intervention from passive response, the problem of control lag caused by thermal inertia is fundamentally solved, the stability and comfort of indoor temperature are remarkably improved, and meanwhile energy waste is avoided through accurate compensation.

The invention relates to the technical field of metal smelting, in particular to a metal smelting temperature control method and system. The system comprises a temperature monitoring module, a gas analysis module, a thermodynamic simulation module and a dynamic regulation and control module, the thermodynamic simulation module sets a fitness function according to the Gibbs free energy value, and obtains the optimal temperature and oxygen potential through a particle swarm optimization algorithm; the dynamic regulation and control module is used for converting the theoretical optimal temperature of the thermodynamic model into precise operation, and efficient and stable control over the smelting temperature is achieved. According to the method, the reaction process in the furnace and the current optimal temperature and oxygen potential are accurately controlled on the basis of the Gibbs free energy value and the particle swarm optimization algorithm, the theoretical optimal temperature of a thermodynamic model is converted into precise operation through multi-PID cooperative control, and efficient and stable control over the antimony smelting temperature is achieved; and therefore, the problem that the oxygen-enriched smelting temperature is not accurately controlled is fundamentally solved, the extraction rate of metal is increased, and energy consumption is reduced.