563 results about "Thermal state" patented technology

The invention relates to the technical field of battery thermal management, and provides a dynamic thermal management method and system for a battery module, and the method comprises the following steps: carrying out the local environment heat dissipation capability evaluation when a preset triggering condition is satisfied, and generating an evaluation result; generating a heat dissipation adjustment parameter of the heat dissipation system based on the evaluation result and the current thermal state of the local battery; carrying out data monitoring and recording, and generating reported data information; the reported data information comprises data related to local environment heat dissipation capability evaluation, evaluation result data, heat dissipation adjustment parameter data of a heat dissipation system and battery thermal state change data after the heat dissipation system executes adjustment; and uploading the reported data information to a cloud platform, so that the cloud platform executes continuous learning and optimization operation of the thermal management strategy based on the reported data information. The method has the advantages that the adaptability and safety of heat management are improved, and continuous optimization of a cloud strategy is supported.

The invention relates to the technical field of numerical control, in particular to a control method and system of numerical control equipment and a medium. The method comprises the following steps: collecting workpiece surface temperature distribution data and obtaining a workpiece CAD model; importing the workpiece surface temperature distribution data into a workpiece CAD model for internal temperature conduction inversion to obtain a first workpiece internal temperature distribution diagram; identifying a non-key area of the workpiece; performing a pre-cutting test on the non-key area of the workpiece to collect the temperature in the cutting process; performing nonlinear thermal expansion modeling on the workpiece based on the cutting process temperature to obtain a workpiece thermal expansion characteristic model; and an internal temperature distribution diagram of the second workpiece is obtained, and the internal temperature distribution diagram of the second workpiece represents the initial thermal state of the workpiece before formal machining. The numerical control machining precision and the cooling system efficiency are improved, the machining cost and resource consumption are reduced, and the machining adaptability, flexibility and stability are enhanced.

The invention discloses a waste heat recovery scheduling method and system for a two-phase cold plate of a data center, and relates to the technical field of refrigeration and heat management. The waste heat recovery scheduling method and system for the two-phase cold plate of the data center comprises the following steps that S1, key thermal parameters and tail end state variables are collected through multiple types of thermal monitoring devices, and thermal state monitoring data are obtained and preprocessed; s2, on the basis of the thermal state monitoring data and in combination with an SLA configuration file, performing priority division on the heat utilization terminals, and constructing a scheduling deviation judgment mechanism to identify thermal state changes; s3, under driving of the regulation and control instruction, accessing multi-source waste heat and distributing the multi-source waste heat to each terminal scene, and evaluating a matching condition of the waste heat and a terminal demand; and S4, based on the change of the heat distribution state and the thermal state monitoring data, identifying an overload risk in combination with a multi-parameter linkage mechanism. The problems that waste heat recovery is insufficient and the energy utilization rate is limited under the light-load and multi-heat-source cooperative working condition are solved.

The invention discloses a new energy commercial vehicle fast charging working condition thermal management control method and system, and relates to the technical field of new energy vehicle thermal management and fast charging control, and the method comprises the following steps: collecting the temperature, voltage and current data of each subarea of a battery in a fast charging process, forming a time synchronization sequence, and based on the sequence, obtaining a new energy commercial vehicle fast charging condition; calculating internal thermal resistance and thermal capacity parameters of the battery in real time by using an online identification algorithm, updating a basic thermal model to obtain a corrected thermal dynamic model reflecting actual thermal characteristics of the current battery, importing the corrected model into a model prediction controller, constructing a multi-objective optimization function, and performing rolling solution in a prediction time domain to obtain a prediction model; and outputting an optimal target charging current instruction and a cooling total demand, adjusting the charging power according to the target current, and combining the temperature difference distribution of each partition. Accurate prediction and partition cooperative control of the thermal state of the battery in the fast charging process are achieved, the temperature rise and the temperature difference are effectively restrained while the charging efficiency is guaranteed, the service life of the battery is prolonged, and the system safety is improved.

The invention discloses a battery prefabricated cabin intelligent refrigeration control method and system based on data driving, and relates to the technical field of battery energy storage system thermal management, and the method comprises the steps: collecting the operation multi-source data of a battery prefabricated cabin, and constructing the current thermal environment state expression; constructing a battery cabin short-term internal heat change trend prediction model based on the operation multi-source data of the battery prefabricated cabin; and according to the current thermal environment state expression and the thermal trend prediction result of the battery compartment short-term internal thermal change trend prediction model, an optimal control strategy for an air cooling, liquid cooling or composite refrigeration mode is formulated. According to the method, a closed-loop thermal management system driven by data is formed by constructing a thermal state expression module, a thermal trend prediction module and an intelligent refrigeration decision module, accurate recognition and active regulation and control of the thermal risk of the battery prefabrication cabin are achieved, the temperature control precision and the response efficiency are improved, energy consumption and over-control risks are effectively reduced, and the method is suitable for popularization and application. And the system has the advantages of remarkable engineering practical value and system intellectualization.

The invention provides a multi-section collaborative dynamic adjustment temperature control system and method, and relates to the technical field of multi-section temperature adjusting.According to the multi-section collaborative dynamic adjustment temperature control system and method, division and data acquisition of a screw rod section, a barrel section and a machine head section are achieved through the thermodynamic state of materials of all sections, and after thermodynamic state data of all the sections are obtained, the temperature of the materials of all the sections is obtained; based on shear heat modeling of a compression section, heat source distribution and axial temperature change of a screw area are obtained, a two-dimensional heat conduction model of a barrel section is established, heat flux density in an axial partition structure is continuously solved, flow coupling calculation is further introduced into a machine head area, outlet temperature fluctuation characteristics are extracted, and a heat flow distribution model is established. And finally, by uniformly fusing the output parameters of each section, a dynamic thermal potential energy function is constructed, and the system can realize overall quantification and uniform expression of the thermal state of each temperature control section. The real-time responsiveness and the global heat balance level of the multi-section temperature control system are effectively improved.

The invention relates to the technical field of turret heat management, in particular to a power turret heat management optimization method and system based on intelligent cooling, and the method comprises the steps: obtaining the temperature distribution data and related working condition parameters of a power turret in real time, and building a heat state feature vector representing the dynamic relation between the heat generation and heat dissipation capability of the turret; constructing a cooling decision model, inputting the state vector into the cooling decision model, and generating an initial control strategy; the initial control strategy is simulated and executed in the digital twin environment, and a strategy reconstruction mechanism is triggered when the predicted temperature suppression rate is lower than a set threshold value; and performing real-time dynamic optimization on the verified initial control strategy according to the processing quality constraint and the equipment safety threshold, and superposing the thermal inertia delay compensation amount to generate a final control strategy. According to the method and the device, the problem of temperature control failure caused by thermal inertia time lag is effectively solved, accurate space-time matching of the cooling instruction and the thermal load peak value is realized, and thermally induced deformation is remarkably inhibited.

The invention belongs to the field of aero-engines, relates to an engine main combustion chamber design technology, and provides a ceramic matrix composite material flame tube matching design method and system.The method comprises the steps that a flame tube wall temperature interval of a main working state point is obtained; determining the thermal-state radial dimensions of the feature points on the ceramic-based component and the metal component; converting the hot-state radial size into a cold-state radial size; carrying out two-dimensional cold-state flame tube profile design; and the cold-state radial size of the two-dimensional cold-state flame tube molded surface is converted into the hot-state size to obtain a two-dimensional hot-state flame tube molded surface, and a three-dimensional hot-state model is constructed and evaluated and iteratively optimized. According to the method, matching structure characteristic parameters of the ceramic-based component and the metal component are designed, and the molded surface of the flame tube made of the different materials is self-adaptively formed into smooth transition at main working state points, so that a backflow area is actively controlled, and the problems that the stability of a flow field of a main combustion chamber is influenced and pressure is lost due to different and relative displacement changes in the working process are solved.

The invention provides a same-side input double-shaft compressor tester rotor concentricity reserving method, which belongs to aero-engine tests and comprises the following steps: determining thermal expansion displacement of an exhaust passage and a gear box support structure in a same-side input double-shaft compressor tester, according to the thermal expansion displacement and the axial distance, the thermal expansion displacement of the input flange of the biaxial compressor test piece and the thermal expansion displacement of the output flange of the gearbox are obtained through calculation, and then the estimated cold and hot state concentricity variation is obtained; according to the estimated cold and hot state concentricity variable quantity, the estimated cold state concentricity is calculated by taking the hot state concentricity as zero, and the rotor of the double-shaft compressor tester is arranged according to the estimated cold state concentricity; vibration measuring points and bearing temperature measuring points are arranged for testing, the operation state of the double-shaft compressor tester is judged through the vibration measuring points and the bearing temperature measuring points, and if the operation state meets the requirement, the estimated cold-state concentricity meets the requirement; and if the operation state does not meet the requirement, the estimated cold state concentricity is corrected.

The invention relates to the technical field of permanent magnet motor speed regulation, in particular to a speed regulation control system of a permanent magnet motor, which realizes high-dimensional accurate description of the running state of the motor by identifying the magnetic performance change of a permanent magnet under different thermal state conditions and combining the structural change characteristics of a motor winding. Response consistency and error convergence performance of control gain adjustment are remarkably improved, a proportional integral factor value group is obtained by adjusting an interval gain sequence, ordered switching path planning between operation states is achieved, abnormal states are found in advance, an excitation fluctuation source is accurately positioned, and by constructing a voltage excitation adjustment set, the control gain adjustment accuracy is improved. The method effectively improves the flexible adjustment capability and the abnormity response rate of a control strategy, achieves the multi-time-domain, multi-segment, quick response and stable speed regulation of the permanent magnet motor under a complex working condition, remarkably improves the dynamic adaptive capability and the output control precision, and reduces the energy consumption and response lag.

The invention relates to the technical field of cold box control methods, in particular to a rapid and stable control method and device for a cold box. According to the technical scheme, the system comprises a cold box historical state feature library, a dynamic feed-forward compensation calculation module and a cooperative control output module; the method specifically comprises the following steps: S1, constructing a cold box historical state feature library; and S2, historical state modeling and dynamic feed-forward compensation control strategy. The feed-forward dominant control is performed by using the historical optimal moving trajectory, so that the valve can be adjusted more actively and more closely to the actual thermal state of the cold box, and the time required for the cold box to reach the target stable working condition is remarkably shortened. The temperature control stability and safety are remarkably improved, the risks of cracks, leakage and even damage of equipment are greatly reduced, and the service life of the cold box is prolonged; the comprehensive utilization efficiency of applications such as liquid-air energy storage is improved; and by reducing the risk of thermal stress damage, the equipment maintenance cost and the accidental shutdown loss are reduced.

The invention relates to the field of digital twinborn technology and industrial equipment intelligent operation and maintenance, and discloses an electric power screen cabinet heat dissipation efficiency improvement and thermal management comprehensive analysis system, which comprises an offline modeling module for constructing a thermal order reduction model with efficient calculation through a model order reduction method based on high-fidelity CFD simulation data; the real-time data acquisition module is used for acquiring real-time power consumption, sparse sensor temperature and an expected load curve; the online state estimation module is used for fusing physical prediction of the thermal reduced-order model with real-time sparse measurement data and reconstructing a global three-dimensional temperature field of the power screen cabinet in real time; and the prospective scheduling analysis module is used for taking the current global temperature field as an initial condition, driving the thermal reduced-order model to perform prospective deduction by utilizing an expected load curve, and calculating and outputting a future thermal margin to early warn a thermal risk. According to the invention, comprehensive real-time sensing, prospective risk prediction and self-adaptive correction of the thermal state of the electric screen cabinet are realized, and thermal management is converted from passive response to active prevention.

The invention relates to the technical field of intelligent detection, and discloses a high-temperature alloy casting size on-line detection system based on machine vision, and the system comprises an imaging fusion module which collects image data of a high-temperature alloy casting, carries out the pixel-level registration of infrared image data and visible light image data, and generates a multispectral fusion image. The feature extraction module performs temperature distribution analysis and brightness feature extraction based on the multispectral fusion image, generates an edge confidence map and extracts a feature point set. And the calculation module performs weighted fitting on the feature points according to the feature point set to obtain thermal state size parameters. And the thermal compensation module performs thermal compensation and geometric correction on the thermal-state size parameters to obtain cold-state size parameters. And the judgment module carries out comparison to judge whether the casting is a qualified casting. According to the invention, stable imaging and accurate registration in high-temperature radiation and strong reflection environments are realized, and the detection efficiency and the size control level of the high-temperature alloy casting are improved.

The invention discloses a numerical control machine tool machining state monitoring method and device, and belongs to the technical field of digital machine tool control. The method comprises the following steps: step 1, constructing a double-layer sensing network system consisting of an environment layer and a machine tool layer, and realizing preliminary physical isolation of environment parameters and a machine tool thermal state; 2, forming a multi-dimensional parameter mapping library of environmental influence and self-heating; 3, decomposing the temperature change signal into a low-frequency environment component and a high-frequency processing thermal response component, respectively extracting environment characteristics and processing characteristics in the low-frequency environment component and the high-frequency processing thermal response component, and realizing real-time classification and decoupling of the temperature signal; 4, constructing a heat influence cross matrix, and quantitatively describing the influence degree and interaction effect of the environmental parameter change and the machine tool heating on the precision of each shaft; and 5, designing a dual-channel parallel compensation control mechanism based on an analysis result of the thermal influence cross matrix, generating a final compensation instruction, and implementing and executing the final compensation instruction to realize precision stable control.

The invention relates to the technical field of electric vehicle thermal management, discloses an electric vehicle motor and driver integrated intelligent cooling system and a control method, and aims at solving the problems that an existing motor driver thermal management system is low in cooling efficiency, high in energy consumption, complex and insufficient in space utilization rate. The method comprises the following steps: acquiring operation, thermal state and environment data; constructing a collaborative thermal model and predicting a thermal load; generating an optimal cooling strategy based on the predicted value and the target; the cooling liquid pump, the three-way valve and the cooling fan are adjusted, and cooling resources are dynamically distributed to achieve collaborative cooling. The system comprises a data acquisition module, a collaborative thermal model construction prediction module, an intelligent decision control module and an integrated cooling circulation execution module. By the adoption of the technical scheme, the cooling performance can be effectively improved, system energy consumption and complexity are reduced, space layout is optimized, the service life of parts is prolonged, and the reliability, the power performance and the endurance of the whole vehicle are improved.

The invention discloses a heat dissipation drum brake dynamic control system and method based on reinforcement learning. The method comprises the following steps that S1, drum brake operation data are collected and preprocessed; s2, training by using a gating circulation unit neural network, and outputting temperature rise trend data; s3, training based on a near-end strategy optimization algorithm to obtain a control strategy network, and outputting a heat dissipation control strategy; s4, performing joint optimization on hyper-parameters of the thermal state prediction model and the control strategy network by adopting a Harris eagle optimization algorithm; s5, generating a heat dissipation control instruction according to the optimized model, and controlling a heat dissipation execution mechanism to execute corresponding operation; and S6, continuously collecting temperature feedback data, comparing the temperature feedback data with the temperature rise trend data, and carrying out dynamic adjustment. Through fusion of reinforcement learning, deep prediction and intelligent optimization technologies, accurate prediction and dynamic heat dissipation control of the temperature rise trend of the drum brake are realized, so that the safety, the energy efficiency and the stability of a brake system are remarkably improved.

The invention discloses a hospital public building temperature refined energy-saving regulation and control method, which comprises the following steps: establishing a refined hierarchical management architecture based on use requirements and energy use purposes of different wards; for a conventional inpatient ward, door and window opening and closing state data and ward heat state data are collected, and air conditioner operation control and door and window opening and closing state adjustment are executed based on a window magnetic control air conditioner operation model and by adopting a multi-step prediction control method; for different types of special wards, regulating and optimizing corresponding thermal equipment by adopting a multi-step prediction control method under an MPC model prediction control framework according to thermal parameters required to be controlled by the current type of ward; for outpatient wards, outpatient air conditioner output operation is optimized by adopting a multi-step prediction control method based on a cooling load prediction model according to the flow density, the temperature and the indoor and outdoor temperature difference; according to the invention, monitoring and accurate prediction of the thermal condition in the ward are realized based on the model prediction control MPC method in combination with the window magnetic switch.

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.

The invention provides a cold-state blade tip gap design method which comprises the following steps: S1, establishing a blade thermal-state design model and a flow field grid, and enabling the blade thermal-state design model to have an equal blade tip gap structure; s2, converting the blade thermal state design model into a cold state blade initial model; s3, calculating the thermal-state radial deformation of the blade tip by using a computational fluid mechanics method; and S4, subtracting the blade tip thermal-state radial deformation from the blade tip height of the blade thermal-state design model to obtain a cold-state blade correction model. According to the method, the local height and the surface shape of the blade tip of the turbine movable blade in the cold state are obtained through reverse deduction by calculating the local deformation of the blade in the main working state of the turbine movable blade, and therefore it is guaranteed that the blade tip gap is uniform in the working state of the movable blade.

The invention provides a spindle constant-temperature AI closed-loop heat engine system, and relates to the technical field of numerical control machine tool control and heat management. The invention aims to solve the problems of response lag, uncontrollable thermal stress, single heating strategy and the like of the traditional spindle heat engine method. The system comprises a multi-dimensional thermal state sensing module used for constructing a multi-node discrete temperature field representing the overall thermal distribution of the main shaft; the real-time heat balance feedback module is used for judging the cold / hot starting state of the main shaft according to the initial temperature difference and executing a differentiated feedback control strategy; and an AI prediction forward compensation module that predicts a future cutting thermal load by pre-reading a machining instruction and generates a feedforward thermal compensation instruction. According to the method, the thermal stress is controlled by introducing the radial thermal gradient index as the safety constraint, negative precooling or positive preheating is achieved in combination with the AI predictive capacity, a feedback and feedforward composite control mode is formed, and the dynamic thermal stability and the machining precision of the main shaft under the complex working condition are improved.

The invention discloses a system for preparing a green cementing material by thermal coupling of metallurgical slag. Comprising a reaction furnace for receiving the hot blast furnace slag and the hot steel slag, and a stirring device for stirring the hot slag in the reaction furnace, the cooling and granulating system is used for receiving the hot-state slag from the reaction furnace and carrying out cooling and granulating treatment on the hot-state slag; and the grinding system is used for receiving slag particles from the cooling and granulating system and carrying out grinding on the slag particles. According to the system for preparing the green cementing material through metallurgical slag thermal-state coupling, after steel slag is subjected to thermal-state coupling modification, the cementing activity of steel slag micro powder is remarkably improved, especially the early activity is greatly improved, and the S95-level performance requirement of the slag micro powder is met; the content of f-CaO in the steel slag is greatly reduced, and the problem of volume stability of a steel slag product is solved. The invention further discloses a method for preparing the green cementing material through metallurgical slag thermal-state coupling.

The invention belongs to the technical field of new energy vehicle thermal management application, and particularly relates to a new energy vehicle thermal management system intelligent regulation and control method based on artificial intelligence, which comprises the following steps: constructing a dynamic space-time diagram and multi-physical field perception, defining a multi-source sensor data battery monomer, a motor winding and an air conditioner air outlet thermal assembly as space-time diagram nodes, the thermal coupling strength is represented through a dynamic adjacency matrix, the problem of multi-physics field splitting modeling in a traditional method is solved, and space-time diagram convolution is constructed by using a graph attention network and a gating cycle unit to output space-time diagram features. A CFD-PINN thermal load prediction model can be differentially calculated, a Navier-Stokes equation is used as a hard constraint to be embedded into a neural network, it is ensured that a prediction result strictly conforms to the thermodynamic law, a meta-strategy network generates a target weight according to the state, multi-target adaptive optimization is achieved, a lower-layer control instruction changes the actual new energy vehicle thermal state and feeds back the actual new energy vehicle thermal state to an updated space-time diagram, and a new energy vehicle thermal load prediction model is obtained. And closed-loop control is formed.

The invention relates to a surge margin prediction method and device of a gas compressor, equipment and a storage medium. The method comprises the steps that key parameter point sets obtained through load step iteration of the gas compressor in all the operation stages are obtained, all the key parameter point sets are mapped to performance diagrams of temperature identification to obtain corresponding mapping performance diagrams, discrete points in the same temperature layer in all the mapping performance diagrams are fitted, and the corresponding mapping performance diagrams are obtained; and the thermal state performance curves of the gas compressor in all the operation stages are determined, the surge critical points of all the thermal state performance curves are obtained, the predicted surge margin of the gas compressor in all the operation stages is determined according to the surge critical points of all the thermal state performance curves and all the key parameter point sets, and load step iteration is achieved based on multi-physics field coupling of the gas compressor. By adopting the method, the surge margin of the gas compressor in different operation stages can be predicted based on the key parameter point set obtained by load step iteration realized by considering multi-physics field coupling in each operation stage of the gas compressor, so that the accuracy of a prediction result is improved.

The invention discloses a virtual sensing method for thermal characteristics of an internal combustion engine. The method comprises the following steps: S1, acquiring temperature distribution data; s2, time sequence temperature data mapping; s3, acquiring fusion temperature data; s4, obtaining thermal characteristics; and S5, abnormal judgment of a combustion chamber, an exhaust pipeline and a cooling system. According to the method, the comprehensiveness and the accuracy of thermal state analysis are remarkably improved by constructing a global sensing system of a three-dimensional space temperature field of the internal combustion engine and combining a multi-source sensor collaborative acquisition and deep learning feature fusion mechanism. Through closed-loop coupling of time-space sequence temperature data and a thermodynamic mechanism model, quantitative correlation between thermal characteristics and combustion efficiency, heat energy loss and cooling efficiency core performance parameters is established. According to the LSTM-CNN-MLP collaborative framework, the spatio-temporal evolution law of a temperature field is extracted in a self-adaptive mode, and the robustness of thermodynamic state perception is remarkably enhanced.

The invention belongs to the technical field of new energy automobile charging equipment, and relates to a charging pile power adaptive adjustment system and method based on temperature feedback, and the method comprises the steps: carrying out the data fusion of a plurality of collected temperature values through employing a Kalman filtering algorithm, and obtaining a target temperature fusion value representing the overall thermal state of a charging pile; the target temperature fusion value is compared with a preset temperature safety threshold value, and the output power of the charging pile is dynamically adjusted according to a comparison result; the future temperature trend is predicted through a charging pile internal temperature prediction model and an air cooling / liquid cooling cooperative temperature adjustment mechanism, and a system can take actions in advance before the temperature does not reach a dangerous threshold but is determined to exceed the standard, so that the passive situation of traditional thermal management is thoroughly changed, real preventive control is realized, and the safety of the system is improved. The output power can be actively reduced when it is detected that the temperature in the pile rises, and overheating damage is prevented; and when the temperature returns to normal, the original power is automatically recovered, so that the reliability and the service life of the charging pile are improved.

The invention discloses a building energy consumption control method. The method comprises the following steps: acquiring thermal state data of equipment; based on the thermal state data, a quantitative thermal urgency index fusing static temperature difference, dynamic change and instant demand dimension is generated; and performing cooperative scheduling on the communication resources allocated to the equipment according to the quantitative thermal urgency index. According to scheduling, candidate communication links are scored through a multi-dimensional evaluation system at least comprising a thermal cooperation dimension, a target link is determined through marginal utility evaluation under dual budget constraints of communication energy consumption and equipment power, and a communication resource scheduling scheme comprising time slot allocation and power authorization is generated and executed. According to the method, the physical state requirement of the equipment is deeply coupled with communication resource scheduling, collaborative optimization of cross-domain resources is realized, and the response speed and the overall energy efficiency of building energy consumption control are improved.

The invention relates to the technical field of power electronic conversion, and discloses a high-efficiency rectification conversion system and a control method thereof, and the system comprises the following modules: a detection module, an input compatible module, a hybrid power device module, a control module, a thermal management module and a frequency modulation module. The control method comprises the following steps: acquiring input power grid voltage, output current and load state parameters; calculating an input voltage phase difference; dynamically selecting the type and channel configuration of the silicon carbide or gallium nitride power device according to the load rate; outputting a device configuration instruction and a switching frequency control instruction; adjusting the cooling system through the evaluated thermal state of the conversion system; and the control module receives the control instruction output by the control module and is used for implementing a corresponding pulse width modulation strategy. According to the method, a multi-system power grid identification and self-adaptive topology switching strategy is adopted, the technical effect of automatically configuring the optimal rectification architecture under different input types is achieved, and the problems of response delay and poor compatibility of the method in the environment of variable power grid types are solved.

The invention discloses a heat dissipation control method and device, equipment, a storage medium and a program product, relates to the technical field of server heat dissipation, and can monitor the heat state of a server in real time by obtaining current data of a heat dissipation component. Then, the data are input into a pre-established heat dissipation model, and the model is based on a heat balance equation and a state-space equation of a server and can accurately predict the temperature adjusting amount. Therefore, the system can actively adjust the heat dissipation strategy instead of passively responding to the temperature change, dependence on experimental data is reduced, and complex PID parameter adjustment is avoided. Dynamic control is carried out according to the temperature adjusting quantity, the system can quickly respond to temperature changes, optimize the rotating speed of the fan and reduce energy consumption, meanwhile, the operation stability and reliability of the server are improved, the technical problem of heat dissipation control is solved, and the technical effect of heat dissipation control is achieved.

The invention discloses a hybrid power vehicle collaborative thermal management method and system based on energy flow intelligent perception. The method comprises the following steps: sensing and predicting multi-dimensional energy flow characteristics of an engine in real time through a pre-trained time sequence neural network model; the predicted value is used as a feedforward signal, real-time temperature feedback of the power battery is combined, and a thermal management cooperative control instruction is generated through feedforward-feedback cooperative decision logic; and finally, a heat exchange path between the engine cooling system and the battery heat management system and respective execution mechanisms are dynamically adjusted, so that prospective active cooperative temperature control is realized. The problems of passive response, control delay and low energy efficiency of an existing thermal management system are solved, and accurate and efficient two-way optimization management of the thermal states of the engine and the battery is achieved.

The invention discloses a mass concrete construction temperature control anti-cracking integrated system and method, and the system comprises a construction module which is used for constructing a cooling water pipe fine model based on concrete thermodynamic parameters and construction conditions, solving a heat flow coupling control equation through a heat flow coupling algorithm, and determining a concrete internal temperature field and stress field distribution cloud chart; the monitoring module is used for collecting attribute data of concrete; the comparison module is used for comparing the attribute data with the concrete internal temperature field and stress field distribution cloud atlas, correcting model parameters of the heat flow coupling model according to a comparison result, generating a regulation and control instruction and sending the regulation and control instruction to the execution module; the execution module is used for receiving and executing the regulation and control instruction; the regulation and control instruction comprises at least one of temperature regulation and pouring time sequence optimization. A temperature field and a stress field are accurately predicted, complex construction working conditions are matched, mechanical and thermal state changes of the whole life cycle of concrete are captured in real time, temperature control adjustment is effectively conducted, and the construction quality is improved.