1569 results about "Thermal load" patented technology

The invention discloses a water-cooling energy consumption adaptive regulation and control method suitable for a data center, and the method comprises the following steps: obtaining a multi-dimensional operation parameter set of the data center in real time, and generating a real-time thermal load density distribution diagram reflecting the heat distribution condition in a machine room; calculating the overall thermal deviation degree and the local hot spot intensity, and solving through a dynamic energy efficiency optimization function to obtain a target system supply and return water temperature difference and a target cooling liquid flow; inputting into a hydraulic and thermodynamic simulation model, and generating an optimal multi-device coordinated regulation instruction set; and executing the multi-device coordinated regulation instruction set, and then performing parameter calibration on the hydraulic and thermodynamic simulation model. The method has the following advantages and effects that the thermal environment of the machine room can be sensed in real time, the energy consumption and heat dissipation requirements can be intelligently balanced, and multiple devices in the cooling system can be cooperatively regulated and controlled, so that the overall energy consumption of the cooling system is optimized while the local overheating risk of the machine room is thoroughly eliminated.

The invention relates to the technical field of temperature control of high-precision industrial heating equipment, in particular to an anti-interference precise temperature control method and system for heating an upper die, and the method comprises the steps: starting a multi-region heating array, heating the upper die to a target temperature according to a preset temperature rise curve, and building a uniform thermal field; before the high-pressure medium is introduced, heat load change caused by the high-pressure medium is predicted based on medium process parameters; in the medium introduction process, dynamic anti-interference compensation control is executed, a feedforward power compensation instruction based on a thermal load and a feedback power fine tuning instruction based on temperature deviation are generated respectively, and the feedforward power compensation instruction and the feedback power fine tuning instruction are weighted and fused into a composite power driving signal for adjusting a heating array; when the temperature fluctuation converges to a stable threshold value, the feedforward compensation weight is gradually reduced, smooth switching to steady-state control is achieved, transient thermal shock caused by a high-pressure medium is effectively restrained through feedforward and feedback cooperative compensation and dynamic weight adjustment, the temperature fluctuation is reduced, and the temperature control precision and stability are improved.

The invention relates to the technical field of data processing, in particular to an induction cooker data acquisition and processing system which comprises a power jump identification module, a response section correction module, a trend sampling analysis module, a temperature control abnormity judgment module and a working condition balance data calibration module. According to the method, the rate change value between the power sampling points in the operation period is calculated, the sections with obvious abrupt change characteristics are screened, and the power lag response is corrected in combination with the voltage change slope, so that the time offset between the control response and the electric signal change is effectively corrected; the temperature fluctuation trend and the temperature control deviation direction are analyzed on the basis of the correction sequence, a temperature control abnormal state label set is formed by matching current waveform symmetry characteristics, a basis is provided for output power adjustment according to the temperature rise rate, the adaptation capacity of data analysis to actual working conditions and the execution precision of a control strategy are improved, and the accuracy of data analysis is improved. And the stable operation capability of the electromagnetic heating equipment under the complex thermal load change is enhanced.

The invention discloses a data center machine room energy-saving optimization method and system based on thermal environment prediction. The method comprises two stages of offline modeling and online prediction optimization. In the off-line stage, a CFD simulation model is constructed based on a machine room physical structure, equipment layout and thermal load parameters, and high-precision temperature field data is generated; using the thermal environment prediction model to input equipment parameters and load change to output future space temperature distribution; meanwhile, an XGBoost hybrid energy consumption prediction model is constructed based on the wind speed ratio or the fan frequency, the number of running fans and related characteristics. In the online stage, the lowest energy consumption and the minimum temperature deviation serve as targets, and a Pareto optimal solution set is generated through an MOEA / D algorithm; the optimal wind speed ratio / frequency and equipment number combination is selected as required to control operation of the air conditioner; and dynamically updating model parameters by sliding a time window to realize long-term robust control of the system. According to the method, intelligent energy-saving control of the machine room is realized by fusing CFD simulation, time sequence prediction, energy consumption modeling and a multi-objective optimization algorithm.

The invention is suitable for the technical field of intelligent control, and discloses a water cooling control method, system and device and a medium. Based on the preprocessed data, constructing a thermal load trend prediction model based on LSTM to obtain a cold load prediction value; based on the cold load prediction value, a PID adjusting signal is generated in combination with the temperature error value; based on the PID adjusting signal, a water pump target frequency instruction is obtained in combination with the cooling load predicted value; based on the water pump target frequency instruction, a valve target opening instruction is obtained in combination with the actually-measured water flow; based on the valve target opening instruction, the fault alarm and emergency instruction is generated, the preset emergency measures are executed, the PID control parameters are updated, the performance evaluation report and the feedback information are obtained, and the response speed, the operation stability and the autonomous decision-making capacity of the water cooling system under the dynamic load and abnormal working conditions are improved.

The invention relates to the technical field of data center thermal management, and discloses a data center liquid cooling precise temperature control method and system, and the method comprises the following steps: pre-analyzing a calculation task to generate a power consumption prediction sequence; combining the power consumption prediction sequence with the real-time state information of the liquid cooling system, calculating the heat cost of the task at each candidate calculation node through a digital twin model, and selecting a target execution node according to the heat cost; inputting the power consumption prediction sequence and real-time state information into a reinforcement learning controller, and generating a composite coordination action containing a flow regulation instruction and a dynamic power consumption upper limit instruction; and cooperatively controlling the micro-fluidic execution array and the chip power consumption management unit on the target execution node according to the composite coordination action. Through prospective power consumption prediction and two-way cooperative control from the heating end and the heat dissipation end, intelligent distribution and accurate temperature control of thermal loads are achieved, temperature overshoot is effectively restrained, and the overall operation energy consumption of the data center is reduced while the system reliability is guaranteed.

The invention relates to the technical field of vapor-liquid two-phase cooling, and discloses a vapor-liquid two-phase cooling method and system based on phase change immersion. The method comprises the following steps: acquiring a multi-modal monitoring data set of a target cooling system; performing spatial gradient feature extraction, transient response analysis and motion mode analysis processing on the data to obtain a temperature field feature matrix, a thermal load fluctuation vector and a bubble dynamics feature sequence; performing multi-physical field coupling processing on the features to generate a fusion cooling state feature set; a pre-configured multi-phase flow simulation model is called to carry out cooling efficiency evaluation, and a cooling efficiency index set containing the correlation mapping relation between the working medium flow characteristics and the heat exchange efficiency is generated; performing collaborative anomaly traceability processing based on the mapping relationship, and generating a phase change anomaly traceability report for identifying an abnormal boiling region and a working medium flow defect mode; and generating a cooling parameter self-adaptive control strategy according to the traceability report, and sending the cooling parameter self-adaptive control strategy to a cooling control system to execute real-time parameter adjustment.

The invention discloses a layered micro-channel liquid cooling method and system based on a magnetic suction interface, and relates to the technical field of micro-channel liquid cooling structures. The layered micro-channel liquid cooling method and system based on the magnetic suction interface comprises the following steps: S1, acquiring and preprocessing temperature characteristic data and fluid flow velocity pressure data, and constructing a standardized thermal load trend data set; s2, the cooling liquid supply state of each layer is evaluated, and the liquid supply rhythm of the corresponding layer is dynamically adjusted; s3, analyzing the cooling demand intensity of each layer, and driving the working frequency of the branch pump of the corresponding layer to change; and S4, evaluating the coordination state of each layer in the process from liquid supply to heat dissipation to liquid return, and dynamically adjusting the liquid cooling control strategy. The problems that in a multi-layer server structure, an existing liquid cooling distribution path cannot achieve dynamic flow adjustment according to the thermal load difference of each layer of equipment, so that cooling resource distribution is uneven, and energy consumption waste is serious are solved.

The invention relates to the technical field of direct current charging pile liquid cooling heat dissipation control. The invention provides a cooperative control method, system and device for a direct-current liquid cooling charging pile and a storage medium. The method comprises the following steps: collecting charging current, gun line temperature, power module temperature and environment temperature; respectively constructing improved prediction function control sub-models of the gun line temperature and the power module temperature, and generating corresponding liquid cooling oil flow velocity control signals; heat dissipation control is carried out on the gun line and the power module through the liquid cooling machine execution unit; actual temperature is collected in real time and compared with predicted temperature to obtain an error, a control signal is corrected according to the error, and an optimal control mode is selected by adopting a mode switching strategy; and according to the current thermal load state, dynamically distributing the weight output by each sub-model, and adjusting the control priorities of different heat dissipation objects to realize collaborative heat dissipation. The problems of unbalanced heat dissipation, response lag and low energy efficiency caused by lack of cooperative control of a plurality of heat dissipation objects in an existing direct current charging pile liquid cooling heat dissipation technology are solved.

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 source-grid-load-storage integrated coordinated management and control system for an intelligent micro-grid, and relates to the technical field of intelligent micro-grids and comprehensive energy regulation and control. The system comprises the following components: a multi-energy-flow data acquisition unit, a multi-energy-flow coupling modeling and optimizing unit, a multi-energy-flow gradient utilization execution unit, a mode self-adaptive switching unit and a main control unit, according to the invention, through a multi-energy flow coupling modeling and optimization unit, an electric-thermal-gas multi-energy flow coupling model comprising a heat supply network transmission loss calculation sub-model is constructed, a renewable energy consumption constraint sub-model is additionally arranged, and an improved hybrid particle swarm optimization algorithm is adopted to carry out dynamic optimization solution, so that an optimal scheduling strategy is generated; according to the strategy, the consumption rate of renewable energy sources is increased, electricity-heat gradient utilization and efficient configuration are achieved through a heat energy distribution priority regulation and control mechanism and efficiency optimization control of the waste heat recovery module, and dependence of heat loads on electric energy is remarkably reduced.

The invention relates to the technical field of artificial intelligence and equipment control, and discloses an AI-driven commercial refrigerator dynamic energy-saving and load prediction system, which comprises the following steps: circularly multiplexing the working and shutdown of a compressor into an active detection process for the thermodynamic state of a refrigerator, and calculating the temperature of the refrigerator according to the temperature time sequence data generated in the process; according to the method, multi-scale dynamic characteristics capable of representing the total heat load and the heat exchange efficiency at the same time are extracted, a machine learning model is input for working condition classification, and then self-adaptive adjustment of a control strategy is achieved. The insight from the passive response to the single temperature to the core hidden variable of the dynamic thermal load is realized, so that the control system can identify the real working condition and make the optimal energy-saving decision, and the energy efficiency and the operation reliability of the equipment in the complex dynamic environment are improved.

The invention discloses a charging pile liquid cooling module intelligent cooperative control system based on an industrial Ethernet, and relates to the technical field of liquid cooling control. The charging pile liquid cooling module intelligent cooperative control system based on the industrial Ethernet comprises a liquid cooling data acquisition and preprocessing unit used for acquiring and preprocessing liquid cooling cooperative operation data; the thermal load sensing and intelligent liquid cooling regulation and control unit is used for dividing independent cooling branches, evaluating the thermal load degree of each cooling branch, judging the real-time thermal load state and generating and executing a control instruction; the anomaly detection and cooling redundancy control unit is used for evaluating the thermal response deviation condition of a cooling branch and judging whether a double-ring redundancy pipeline is started or not; and the fault root cause judgment and recovery enhancement unit is used for evaluating the component fault risk degree in the abnormal branch and executing fault-tolerant control and branch recovery strategies. The problem that a whole set of liquid cooling system is shut down due to the fact that local fault tolerance cannot be achieved when a local branch breaks down in a traditional pipeline structure is solved.

The invention belongs to the technical field of intelligent heat supply, and provides a green power consumption heat storage and release matching control method and system based on a water heat storage boiler, and the method comprises the steps: firstly obtaining a heat load prediction sequence and an electric power spot market price prediction sequence of a heat supply system; secondly, regarding the heat supply network as a graph structure composed of nodes and pipelines, and establishing a pipe network dynamic model for describing the hydraulic and thermal characteristics of the heat supply pipe network; and finally, with the purpose of minimizing the comprehensive operation cost of the heat supply system in the whole scheduling period, and with the whole network heat balance, heat source operation, centralized heat storage device operation, heat supply network safety and user comfort as constraint conditions, solving to obtain a source network load storage cooperative control strategy. The purpose of integrated collaborative optimization of the heat source, the energy storage, the pipe network and the load is achieved, a scheduling strategy with better economical efficiency can be generated, and the problems that the absorption capacity is insufficient, and the overall operation economical efficiency of the system is not high are solved.

According to the data center evaporation cold total heat recovery double-energy-storage air conditioning system and the control method, the obvious energy efficiency improvement and economic optimization effects are achieved, the future server heat load, environment parameters and electricity price changes are accurately pre-judged through a composite prediction model of the central control module, and the real-time charge state of the double-energy-storage module is combined, so that the energy efficiency is improved. A collaborative operation instruction with the optimal cost is generated; by means of deep coupling of the evaporative cooling module and the total heat recovery module, a natural cold source is utilized to the maximum extent, and the running time of a conventional refrigeration module is shortened; through cooperative scheduling of the cold energy storage unit and the heat storage unit, efficient cold / heat storage is achieved in the electricity price valley value period, stored energy is released preferentially in the peak value period, and frequent starting and stopping of equipment are avoided; and on the basis of the multi-dimensional constraint optimization decision model, the total operation cost is minimized on the premise that the system meets the safety temperature and humidity requirements of the data center.

The invention relates to the technical field of building energy saving, and discloses an energy room intelligent control method and system facing the sunlight condition, and the method comprises the steps: obtaining the total solar radiation intensity and scattered radiation intensity through a distributed sensor disposed in an energy room; calculating a sunlight illumination component proportion based on the total solar radiation intensity and the scattered radiation intensity, and determining a sunlight type according to the sunlight illumination component proportion; according to the sunshine type, the influence of sunshine change on the indoor thermal environment is evaluated by adopting a prediction algorithm branch, and the indoor temperature and humidity change trend and the thermal load demand in the future time period are predicted; based on the indoor temperature and humidity change trend and the heat load requirement in the future time period, combined with the heat mass energy storage level of the energy house building, a comprehensive regulation and control instruction matched with the sunlight type is generated; and according to the comprehensive regulation and control instruction, regulating and controlling the heat mass storage and release of the sunshade device, the ventilation system and the building, monitoring the regulation and control effect in real time, and optimizing the prediction algorithm according to the regulation and control effect. And regulation and control of the energy house under the sunlight condition are realized.

The invention discloses a panel lamp light source integration system based on a flexible circuit board, and relates to the technical field of panel lamp light source integration. Generating an initial design drawing of the flexible circuit board containing a plurality of layers of conductive circuits and a plurality of light source bonding pads; the channel configuration module configures a driving control channel for the bonding pad and establishes a mapping table with the lighting function area; the thermal load optimization module calculates power consumption and thermal load distribution according to the mapping table and the performance parameters and adjusts routing topology to generate a final design drawing; and the manufacturing and assembling module is used for manufacturing a circuit board according to the drawing and mounting a micro light source to finish assembling. Wiring is matched with the shape of a panel and the characteristics of a light source during planning, heat distribution optimization is achieved in the layout stage, the number of times of modification is reduced, and local overheating is restrained. According to the invention, high-fit compact integration of the flexible circuit board and the panel lamp is realized, and the assembly efficiency and the operation stability are improved.

The invention provides an intelligent control system and method for a natural cooling heat exchange ventilation unit, and relates to the technical field of energy-saving fans. The optimal operation mode and the natural cooling availability of a target ventilation unit are determined firstly; the expected heat exchange amount of the natural cold side is determined according to the current indoor heat load demand characteristics and the natural cold available capacity, and then a static adjusting instruction of a natural cold side actuator is determined according to the expected heat exchange amount; according to the heat load demand characteristics and the expected heat exchange amount, the mechanical refrigeration demand cold capacity is determined, and then a dynamic adjusting instruction of a mechanical refrigeration side actuator is determined according to the heat exchange efficiency and the mechanical refrigeration demand cold capacity of the mechanical refrigeration unit under the current working condition; and performing coordination control on the actuators on the natural cooling side and the mechanical refrigeration side based on the static adjustment instruction and the dynamic adjustment instruction. According to the scheme, dynamic cooperative control over natural cooling and mechanical cooling of the natural cooling heat exchange ventilation unit under the variable working conditions can be achieved, and therefore the energy efficiency is optimized on the premise that the requirement for indoor thermal comfort is met.

The invention discloses a control method for steam condensate waste heat recovery and waste water heating, a control device for steam condensate waste heat recovery and waste water heating, control equipment and a computer readable storage medium. The thermal load and the logarithmic average temperature difference are calculated based on the energy conservation principle, and the needed heat exchange area is calculated through a logarithmic average temperature difference method. A flow combination scheme of the plate heat exchanger is determined according to the heat exchange area and the flow parameters, a steam condensate side adopts a single flow, and a waste water side adopts asymmetric configuration of double flows or multiple flows so as to adapt to the flow difference of the two sides. In addition, a real-time monitoring mechanism is further established, when the total heat transfer coefficient is decreased by more than 10%, a cleaning program is automatically triggered, continuous and stable operation of the system is guaranteed, and efficient utilization of waste heat resources is achieved.

The invention relates to the technical field of temperature control optimization, and discloses an aviation case liquid cooling heat dissipation temperature control optimization method, system and equipment, and the method comprises the steps: collecting instantaneous temperature data, temperature change rate data and thermal load data through a temperature sensor array on the surface of an aviation case; calculating to obtain an instantaneous temperature deviation value, a temperature change rate deviation value and a thermal load deviation value; generating a temperature tracking prediction value based on the instantaneous temperature deviation value, the temperature change rate deviation value and the thermal load deviation value; and liquid cooling heat dissipation parameter collaborative optimization is executed based on the temperature tracking predicted value, an optimal parameter control strategy is determined, and the flight box liquid cooling pump rotating speed, the adjusting valve opening degree and the heat dissipation fan frequency are synchronously adjusted according to the optimal parameter control strategy, so that intelligent collaborative optimization of the liquid cooling pump rotating speed, the adjusting valve opening degree and the heat dissipation fan frequency is realized; and the stability and the reliability of the aviation case liquid cooling heat dissipation temperature control system are improved.

The invention discloses a ventilation cooling optimization method for an all-hydrogen-cooled gas turbine generator, and relates to the technical field of all-hydrogen-cooled generator cooling, and the method comprises the steps: analyzing cooling demands, calculating loss in combination with a high-frequency start-stop peak regulation working condition, and setting a stator RTD temperature, an iron core temperature and a temperature rise target; an end ventilation structure is designed, the diameter of the fan is optimized, and bar gaps, wind shield holes and inner supporting ring ventilation grooves are formed; optimizing variable air ducts of the iron core, and adjusting the width of the air ducts according to thermal load partitions; cFD coupling simulation verification is carried out, and a loss data simulation flow field and a temperature field are imported; carrying out physical test iterative optimization, manufacturing a prototype model, testing, and adjusting parameters until errors are qualified; operation monitoring and dynamic adjustment are carried out, and a sensor is installed to collect data in real time and adapt to working condition requirements. Cooling uniformity and efficiency are improved, peak regulation start and stop working conditions are adapted, hydrogen parameter change influences are balanced, vibration and cooling are cooperatively controlled, operation and maintenance convenience is improved through modular design, and long-term stable operation of the generator is guaranteed.

The invention relates to the technical field of cold-chain logistics transportation and storage temperature control, in particular to an air compressor vehicle-mounted refrigeration and refrigeration house collaborative temperature control system based on AI scheduling, which comprises a multi-dimensional state sensing module used for collecting real-time temperature field data, environmental meteorological parameters, compressor operation states and goods category information in a refrigerator car and a refrigeration house, and sending the real-time temperature field data to a server; a structured multi-dimensional state vector is output; and the thermodynamic evolution prediction module is used for setting a prediction time domain with a finite length based on the multi-dimensional state vector, and calling and constructing a mathematical model of a heat balance relationship between the refrigerating capacity generated by the operation frequency of the compressor and the environment and the cargo heat load. According to the method, the comprehensive cost function fusing the energy consumption, the cargo quality loss and the equipment wear is constructed, and the hidden quality attenuation is converted into the dominant economic cost by using the Arrhenius model, so that the global operation benefit maximization of the system on the premise of ensuring the cargo safety is realized.

A multifunctional thermal exposure indicator can provide immediate reversible indications of overtemperature as well as irreversible indications of excessive thermal loading. Additionally, the multifunctional thermal exposure indicator can provide semi-reversible indications of undertemperature thermal loading, such as exposure to temperatures below the freezing point of water.

The invention discloses a whole vehicle energy optimization calculation method for heat energy coordination of an electric vehicle, which relates to the technical field of electric vehicles and comprises the following steps: S1, acquiring multi-source information related to the running state of the whole vehicle, the multi-source information at least comprises passenger compartment thermal comfort demand information, battery thermal state information, electric drive system thermal state information, vehicle operation condition information and whole vehicle energy state information; s2, on the basis of the multi-source information, performing unified modeling and priority judgment on heat demands of a passenger compartment, a battery system and an electric drive system at a whole vehicle level, and forming a heat energy coordination decision result reflecting a heat load energy demand relationship under current and target working conditions; according to the whole vehicle energy optimization calculation method for heat energy coordination of the electric vehicle, the energy utilization efficiency and the comprehensive performance of the electric vehicle under complex working conditions are remarkably improved.

The invention discloses a comprehensive energy optimization scheduling method considering combustion of gas turbines with different hydrogen doping ratios, and belongs to the technical field of gas turbines, and the method comprises the steps: constructing a source-network-load-storage integrated combined cooling heating and power comprehensive energy system which covers an energy production layer, an energy conversion layer, an energy storage layer and an energy consumption layer; wherein in the energy consumption layer, electric load is supplied by gas turbine power generation, wind and light direct supply and energy storage discharge in a combined mode, heat load is borne by gas turbine waste heat, a gas-fired boiler and a heat storage system together, the coverage rate of a sensitive area is increased through the ergodicity of a chaotic system, population aggregation is avoided through initial value sensitivity, and it is ensured that all optimization schemes cover a key decision interval; meanwhile, in the algorithm evolution process, through a self-adaptive crossover variation mechanism, early enhancement of sensitive area exploration to capture efficiency inflection points and later fine development and positioning of an optimal solution, the problem of key solution omission of a traditional algorithm is thoroughly solved, and a more accurate hydrogen doping ratio reference is provided for system operation.

The embodiment of the invention provides a thermal power plant waste heat gradient utilization management method and system, belongs to the field of energy and power engineering, and aims at solving the problems that in the prior art, waste heat gradient matching is unreasonable, the low-temperature waste heat recovery efficiency is low, and the system integration degree is insufficient. The method comprises the following steps: constructing a multi-physics field coupling digital twinborn model and performing real-time correction; establishing a dynamic matching matrix of the residual heat source and the heat consumption load based on balance analysis; solving a Pareto optimal operation scheme through a multi-objective optimization model; and generating and issuing a cooperative control instruction. The system comprises a panoramic data sensing module, a digital twin modeling module, a balance and optimization decision module and a cooperative control instruction generation module. Through global optimization and dynamic regulation and control, the waste heat utilization efficiency, the economical efficiency and the equipment reliability are remarkably improved.

The invention provides an air conditioner indoor environment parameter control method and system, and relates to the technical field of air conditioner control. External environment information and internal heat source information such as sunlight intensity data and cloud cover prediction data outside a building and the operation state and real-time power consumption data of large electronic equipment inside the building are obtained; the preset building physical attribute parameters are combined, the predicted total heat load increment of all the areas in the future preset time can be calculated in advance, an adjusting instruction is generated in advance before the indoor environment parameters actually change, the operation state of an air conditioner system executing mechanism is adjusted, accurate and active control can be achieved, and the control efficiency is improved. According to the method, local supercooling or superheating possibly caused by a traditional method is avoided, the comfort consistency of the indoor environment is remarkably improved, meanwhile, the energy utilization efficiency is optimized, and energy waste is effectively reduced.

The invention relates to the technical field of vehicles, and discloses an engine intelligent layered thermal management system and method based on multivariable predictive control, and the system comprises a thermal management execution module, an information sensing module and an intelligent control module; the information sensing module is used for collecting real-time information and sending the real-time information to the intelligent control module; the information sensing module comprises a plurality of sensors and a communication interface, the plurality of sensors at least cover a temperature sensor, a pressure sensor and a flow sensor, and the communication interface is used for obtaining engine torque, rotating speed, fuel injection amount, boost pressure and vehicle speed information; the intelligent control module receives the real-time information sent by the information sensing module, performs thermal load prediction and multi-target optimization calculation to obtain an optimal control sequence, and sends the optimal control sequence to the thermal management execution module; and the thermal management execution module receives the optimal control sequence and calls an execution element to execute a thermal management action.

The invention relates to the technical field of ground source heat pump control, in particular to an intelligent cooperative control system for a ground source heat pump system and building energy management. The method comprises the steps that a data collecting and preprocessing unit collects multiple types of data in real time and preprocesses the data to form system state vectors; the load and power generation prediction unit predicts future cooling and heating load and photovoltaic power generation power of the building through a machine learning regression model and a time sequence prediction model; the operation optimization unit generates an optimal operation strategy of the ground source heat pump based on a depth deterministic strategy gradient algorithm; and the multi-source energy coordinated control unit realizes multi-device coordinated control through multi-target mixed integer linear programming. Through combination of prediction data and an optimization algorithm, a dynamic matching relation between load fluctuation and energy supply is fully considered, and the problems of soil heat imbalance and unstable comprehensive energy efficiency ratio of the ground source heat pump system in a traditional fixed parameter operation mode are solved.

The invention discloses a flow scheduling method and device, a medium and a program product, and relates to the technical field of heat dissipation, and the method comprises the steps: obtaining a video memory access frequency as a main parameter when a parallel computing function is executed, matching with other auxiliary parameters related to heat consumption, distributing a weight, determining a heat load scoring result, and then adjusting a cold plate micro-channel flow distribution coefficient, and determining an opening value of a flow control valve and sending a flow scheduling instruction to the liquid cooling system so as to dynamically adjust the cooling liquid flow of each cold plate micro-channel. In this way, accurate temperature control and heat dissipation of the video memory area of the computing device can be achieved, energy waste caused by unnecessary circulation of cooling liquid is avoided, the heat dissipation efficiency is remarkably improved, energy consumption is reduced, and the service life of the computing device is prolonged; in addition, the mode can autonomously complete full-flow operation such as video memory heat consumption monitoring, score calculation and flow adjustment, intelligent management of the heat dissipation process is achieved, manual operation errors and cost are reduced, and the stability and reliability of operation of computing equipment are guaranteed.