6712 results about "Heat management" patented technology

A computer system implements a unified framework integrating an adaptive elastic funnel (AEF) with a convergent intelligence fabric (CIF) for multi-agent AI collaboration. The system provides a universal multi-modal key-value subsystem for sharing partial computations, implements hybrid placement strategies for dynamic memory management, and incorporates quantum-resistant secure enclaves. The architecture integrates hardware acceleration through GPU-FPGA hybrid caching and neuromorphic processors, applies adaptive energy and thermal management across hardware generations, and implements autonomous flash resource orchestration with multi-dimensional wear management. The system orchestrates tensor workflows using hierarchical scheduling, enables cross-agent collaboration with privacy preservation, and supports continuous learning without catastrophic forgetting. This integration delivers unprecedented computational efficiency and security in high-dimensional decision-making environments while supporting incremental adoption through modular interfaces.

The invention provides a new energy automobile battery thermal management method and system based on big data. The method comprises the steps that real-time data flow and a historical temperature change curve in a battery pack are collected in real time through a distributed sensor array; inputting a pre-trained time sequence prediction model, outputting a predicted temperature change curve and calculating a real-time temperature rise slope; obtaining an environment comprehensive compensation amount according to the environment temperature and the battery health state, and subtracting the environment comprehensive compensation amount from the basic safety threshold value to obtain a dynamic safety threshold value; determining a dynamic temperature compensation amount through a preset slope grading mechanism, and subtracting the dynamic temperature compensation amount from the dynamic safety threshold to obtain an advanced intervention temperature point; and when the temperature of the battery pack reaches the advanced intervention temperature point, a graded cooling system is started, and cooling power grades are dynamically switched according to the growth interval where the real-time temperature rise slope is located. The battery temperature is accurately controlled, and the energy consumption is remarkably reduced.

The invention relates to the technical field of heat management of energy storage systems, and discloses a heat management method of an intelligent distributed liquid cooling energy storage system. The method comprises the following steps: acquiring operation state parameters of a plurality of single batteries and optimizing timestamp synchronization; and processing the temperature data by adopting small-batch time series decomposition, and extracting change trend characteristics and abnormal hot spot positions. And based on the information, optimizing a heat exchange control rule base parameter set through a non-dominated sorting strategy, and generating optimized control parameters and priority rules. And in combination with inlet temperature and flow parameters of the liquid cooling system, a tabu search mechanism is utilized to decide a cooling liquid flow distribution scheme, and a branch control instruction is output. And finally, a flow constraint boundary is dynamically adjusted by adopting an approximate gradient projection technology, and a branch and bound strategy is fused to discretize and optimize a distribution path, so that the branch flow is finely regulated and controlled, and the thermal management precision and reliability of the energy storage system are improved. According to the method, the accuracy, adaptability and stability of thermal management of the liquid cooling energy storage system are improved.

The invention discloses a thermal management strategy management method and system based on an energy storage battery system, and relates to the technical field of battery thermal management, and the method comprises the steps: collecting temperature data, carrying out the preprocessing, generating and recording a measurement result and a convective heat transfer coefficient, taking the measurement result and the convective heat transfer coefficient as the input of a Kalman filter, and outputting an optimal estimation result of a battery. The temperature data refer to the environment temperature and the core temperature of the single battery, based on the optimal estimation result of the battery, establishing a fuzzy rule base for iteration and updating, outputting a dynamic temperature difference threshold value, constructing a three-dimensional thermodynamic potential function, calculating the cosine similarity of a cooling driving force vector and a cooling mode, and correcting the cosine similarity to obtain a cooling driving force vector. The mode switching list is generated, the cooling equipment decision mode is generated, starting judgment and optimization of the cooling mode are carried out, and the intelligent level, safety and energy efficiency ratio of thermal management of the energy storage battery system are remarkably improved.

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.

Provided in the embodiments of the present application are an energy storage apparatus, an energy storage system and a charging network. The energy storage apparatus comprises a container, a control module and a thermal management module, wherein the container comprises a container body and a plurality of battery cells, the plurality of battery cells are accommodated in the container body, and at least one of the dimensions of the container in the length direction, the width direction and the height direction is not equal to a corresponding dimension of a standard container; the control module is used for electrically connecting to the plurality of battery cells to perform electrical control over the battery cells; and the thermal management module is connected to the container, the thermal management module is used for managing the temperature of the battery cells, and at least part of the thermal management module is located at the top of the container. When the total energy of a container is fixed, the container can have a smaller volume, such that an energy storage apparatus occupies a smaller floor area, thereby increasing energy per unit floor area of the energy storage apparatus, and thus increasing the areal energy density of the energy storage apparatus.

The invention discloses a new energy automobile hybrid power system cooperative control device and method.The new energy automobile hybrid power system cooperative control device comprises a multi-source data collection module, a cooperative control center and an execution unit, and the multi-source data collection module transmits collected information data to the cooperative control center; the cooperative control center comprises a data fusion unit, an energy management module, a heat management module and a cooperative decision-making unit, the data fusion unit receives data information of the multi-source data acquisition module, carries out fusion processing, and transmits the data information to the energy management module and the heat management module; the energy management module and the heat management module output a control strategy to the collaborative decision-making unit, and the collaborative decision-making unit judges a correction strategy and then sends a control instruction to the execution unit. The method has the advantages that cooperative control of energy management and heat management is achieved, various dimension data of road conditions, driving behaviors, power states and heat source states are fused, the problem of system unbalance caused by single module optimization is solved, and dynamic cooperation of energy management and heat management is achieved.

The invention discloses a morning orbit computing power satellite, and belongs to the field of aerospace technology and space infrastructure. The satellite comprises a satellite platform and a computing force load arranged on the satellite platform. The satellite platform is provided with a condensation type energy system and a space pump drive fluid loop system. The condensation type energy system adopts an expandable condensation type solar cell array to generate power, switches a power supply mode according to an illumination period and an earth shadow period of a morning and night orbit, and supplies power to computing force loads and platform equipment. The space pump drive fluid loop system adopts an expandable flexible radiation cooling plate for heat dissipation, heat dissipation is conducted on computing force loads through a fluid loop, and a heating assembly is arranged to prevent a working medium from being frozen under the low-temperature working condition. Through the expandable structure and the orbit environment adaptability design, continuous energy supply and effective heat management are provided for the computing power load in the morning and night orbit environment, and high-power-consumption computing power load in-orbit stable operation is supported.

The invention discloses a hydrogen-lithium dual-power system structure optimization design and integrated control method applied to an unmanned aerial vehicle. The method comprises the following steps: constructing a hydrogen-lithium dual-power system of the unmanned aerial vehicle; setting an integrated control strategy according to the hydrogen-lithium dual-power system; the integrated control strategy comprises an energy management strategy and a life and safety management strategy; the energy management strategy comprises a rule-based strategy, a power following strategy and a self-adaptive optimization strategy; the service life and safety management strategy comprises a hydrogen fuel cell protection strategy, a lithium battery health management strategy, a thermal management strategy, a dual-power coupling safety management strategy and a redundancy and fault processing strategy. By optimizing the power system design and the energy management strategy, the mass of the unmanned aerial vehicle device is reduced, the cruising ability, the load capacity and the environmental adaptability of the unmanned aerial vehicle are improved, and optimization processing of the control strategy is achieved.

The invention discloses a dynamic load adaptive charging pile liquid cooling control method, relates to the technical field of thermal management, and solves the problems of temperature prediction deviation, local hot spot leak detection and protective supercooling caused by a simplified thermal model based on fixed parameters and key temperature points under rapid load fluctuation. Parameterization time-varying heat supply network parallel multi-rate observation is constructed, a heat exchange coefficient and node heat capacity are identified and calibrated through recursion with physical constraints, transmission time delay is merged into an extended state in an explicit mode, short-window high-frequency sampling and local temperature field reconstruction are triggered based on residual errors, and the time-varying heat supply network parallel multi-rate observation is achieved. A control sequence is issued in parallel by adopting hierarchical rolling type control with a second-order moment uncertainty constraint; based on the scheme, the short-term temperature field prediction precision and the local hot spot identification capability are improved, and the cooling resource directional utilization efficiency and the charging system operation continuity are remarkably improved.

The invention relates to the technical field of lithium battery energy storage and temperature control, in particular to an electronic radiator intelligent temperature control system based on a lithium battery energy storage cabinet. The system comprises an edge temperature sensing module, a cloud thermal management strategy module, a cloud clustering analysis module, a thermal field topological optimization module, a multi-source thermal feature fusion module, a dynamic temperature control strategy generation module and a grading strategy issuing execution module. An edge temperature sensing module collects real-time temperature data of multiple monitoring points and an edge side preliminary temperature control scene judgment result; the cloud heat management strategy module receives battery pack topology connection data; the cloud clustering analysis module carries out fuzzy clustering on the data to obtain a temperature state and scene discrimination clustering center; the thermal field topological optimization module optimizes a temperature state clustering center in combination with topological data; the multi-source thermal feature fusion module fuses the two clustering centers to form multi-source fusion feature representation; the dynamic temperature control strategy generation module determines a temperature control strategy identifier accordingly, and the grading strategy issuing execution module matches and distributes a gradient temperature control strategy to a heat dissipation actuator.

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 discloses a damping thermal insulation material performance evaluation method and system for a battery pack, and relates to the technical field of battery pack thermal management, and the method comprises the steps: extracting a calibration sample set, applying transient thermal excitation, and collecting an infrared thermal image sequence to extract thermal response features; performing industrial CT scanning to obtain defect quantitative indexes, and forming a calibration data set with the thermal response characteristics; establishing a quantitative correlation model based on the calibration data set, and determining a batch quality threshold according to model output distribution; executing the same excitation and collection on an online sample to be detected to extract the characteristics of the sample, inputting the model to obtain a defect quantitative prediction value, comparing the defect quantitative prediction value with a batch quality threshold, and outputting an evaluation result; when a preset period or a trigger condition is met, a new sample is supplemented and extracted, and newly added calibration data is obtained to update the model and the threshold value. According to the method, accurate material performance evaluation is provided by establishing a quantitative model of thermal response characteristics and defect quantitative indexes, and evaluation consistency and stability are enhanced through a dynamic updating mechanism.

The invention relates to the technical field of battery pack heat management, in particular to a PLC-controlled battery pack heat management device and a PLC control system thereof.The PLC-controlled battery pack heat management device comprises a battery box, a cooling cavity, a temperature control partition plate, exchange holes, a circulating water pipe, an adjusting assembly and a control assembly; the battery box is of a cuboid structure, the cooling cavity is formed in the bottom of the battery box, the temperature control partition plate is installed in the battery box, the exchange hole is formed in the upper face of the cooling cavity, the circulating water pipes are arranged on the two side faces of the battery box, and the adjusting assembly and the control assembly are installed in the temperature control partition plate. A low-temperature liquid medium is introduced into a cooling cavity through a circulating water pipe and then is input into a temperature control partition plate from an exchange port for cooling, and an adjusting assembly arranged in the temperature control partition plate adjusts displacement of an internal telescopic assembly through the temperature of a battery pack, so that the pipe diameter of a cooling flow channel is controlled; and thus, self-adaptive cooling liquid distribution in the whole battery box is realized.

The invention discloses a dynamic thermal management and risk pre-judgment system for a lithium battery energy storage system, and relates to the technical field of lithium battery energy storage, and the system comprises a thermal field monitoring module which generates a real-time three-dimensional thermal field distribution map of a battery pack; the dynamic regulation and control module is used for self-adaptively regulating the heat dissipation power and the refrigerant flow in combination with the charging and discharging states of the battery and the environmental parameters; the risk assessment module is used for constructing a thermal runaway risk grade assessment model and generating a risk probability value; the early warning response module triggers a multi-stage early warning mechanism according to the risk probability value, and is linked with the dynamic regulation and control module to execute an emergency heat dissipation strategy to generate a risk disposal scheme; and the data archiving module is used for storing data. According to the invention, the whole-process intelligent design of monitoring, regulation and control, evaluation, early warning and archiving is provided, the thermal management precision, the risk prevention and control capability and the operation economy of the lithium battery energy storage system are comprehensively improved, and a key technical guarantee is provided for large-scale energy storage application.

The invention relates to the technical field of thermal management control, and particularly discloses a thermal management controller regulation and control method and system based on dynamic thermal inertia prediction. According to the method, the dynamic thermal inertia model is constructed through system identification, and the future temperature field evolution and thermal accumulation risks of the system are accurately predicted. On the basis, a multi-layer nested compensation strategy composed of pre-compensation, main compensation and residual compensation is generated in three dimensions of a compensation angle, a compensation order and a compensation domain, and prospective accurate intervention is achieved. In order to evaluate the control effect, an artifact intensity entropy value is introduced as a quantitative index, and a model and a strategy are corrected in real time through an outer ring optimization mechanism to form self-correction. When continuous thermal unbalance caused by hardware design defects is detected, the system can further start hardware cooperative regulation and control, local heat capacity and a heat dissipation path are optimized fundamentally, cross-level cooperative optimization from a control algorithm to a physical structure is achieved, and finally high-precision, low-energy-consumption and self-adaptive system-level thermal management is achieved.

The invention discloses an intelligent fault diagnosis method, device and equipment and a storage medium, and relates to the technical field of new energy automobile thermal management, and the method comprises the steps: obtaining a sensor collection parameter, vibration feature information and a heat source coupling parameter; inputting the sensor acquisition parameters, the vibration characteristic information and the heat source coupling parameters into a reinforcement learning model to predict a potential fault, and determining a fault type, a fault confidence coefficient and fault evolution trend information; performing fault identification based on the fault type and the fault confidence, and determining fault type information; and generating a corresponding fault correction report based on the fault category information and the fault evolution trend information. According to the method, the potential fault is predicted in advance through the reinforcement learning model, the type, confidence and evolution trend of the potential fault are accurately deduced, a dynamic fault correction report is generated, the fault is intervened in advance, the diagnosis accuracy is improved, and fault diagnosis from passive response to active prevention and considering reliability and energy efficiency is realized.

The invention discloses a new energy vehicle heat management method, device and equipment and a storage medium, and relates to the technical field of new energy vehicle heat management.The new energy vehicle heat management method includes the steps that the vehicle running state, the compressor working state, an air conditioner enabling signal and the battery temperature are obtained; determining a target thermal management mode according to at least one of the vehicle running state, the compressor working state, the air conditioner enabling signal and the battery temperature; operation parameters of a target control assembly are obtained according to the target heat management mode, wherein the target control assembly comprises a compressor, a refrigerant electromagnetic valve, an electronic expansion valve, a fan, a water pump and a PTC heater; thermal management is conducted on a vehicle battery and / or a cab on the basis of the operation parameters, the operation parameters comprise at least one of the rotating speed of a compressor, the state of a refrigerant electromagnetic valve, the opening degree of an electronic expansion valve, the rotating speed of a fan, the state of a water pump and the power of a PTC heater, and the charging efficiency and the system energy efficiency in the low-temperature and high-temperature environments are improved.

The invention discloses a passive radiation refrigeration coating and a preparation method thereof, and relates to the technical field of industrial coatings. Comprising a fluoroacrylate emulsion, hollow glass beads, nano titanium dioxide, flaky silicon dioxide aerogel powder, polytetrafluoroethylene micro powder, hydroxyl-terminated polydimethylsiloxane, a hydroxyl acrylic acid modified silane coupling agent, a super-hydrophobic modified fluorosilicone surface additive, nano cerium oxide, aluminum fluoride doped zinc oxide infrared enhancement powder and deionized water. The paint is prepared on the basis of the formula. According to the invention, a multi-scale spectrum regulation and control and surface self-cleaning system is constructed cooperatively, so that the synergistic effect of high reflection of a sunlight region and high emission of a middle infrared region is realized. The coating can maintain continuous passive refrigeration in a day and night period, the surface of the coating has self-cleaning capability and excellent ultraviolet aging resistance, and high reflectivity and high radiation emissivity can be maintained for a long time in a complex outdoor environment, so that the thermal management efficiency of buildings and equipment is remarkably improved.

The invention relates to the technical field of refrigeration material preparation, in particular to an efficient passive radiation refrigeration material suitable for a sub-super environment and a preparation method and application of the efficient passive radiation refrigeration material. The method comprises the following steps: uniformly mixing thermoplastic polyurethane, sunlight high-reflection inorganic particles and a phase change material in a solvent; after a chemical foaming agent is added, the obtained suspension liquid is heated and foamed in a confinement mold, and wet gel is formed; and finally, carrying out freeze drying treatment to obtain the composite porous aerogel. The prepared material has a micro-nano porous skeleton formed by TPU, and inorganic particles and PCM are uniformly dispersed in the skeleton wall. Through component cooperation and a special porous structure, the material has extremely high sunlight reflectivity and mid-infrared emissivity, self-adaptive temperature regulation and control are achieved through PCM phase change, the problem that refrigeration of a traditional material fails in the sub-environment such as the vertical surface is effectively solved, and efficient sub-super-environment heat management is achieved.

The invention discloses a regulation and control system and method based on heat energy of an energy storage cabinet, and belongs to the technical field of intelligent heat management. Temperature data in the energy storage cabinet are collected, a temperature distribution matrix is constructed, and a thermal gradient vector and an overheating risk area are extracted based on a difference algorithm; further establishing a thermal power load mapping model, and dynamically generating an air circulation path optimization diagram; the opening angle of a flow deflector and the rotating speed of a fan are adjusted in combination with an optimized path, and self-adaptive regulation and control of a thermal field in the cabinet body are achieved; meanwhile, a machine learning model is trained by utilizing historical operation data, an optimal regulation and control strategy is output, and an execution layer is driven to realize collaborative response of a fan and a flow deflector; the method has the advantages of high regulation and control precision, high response speed, low energy consumption and the like, and is suitable for heat management requirements of various types of energy storage cabinets.

The invention relates to the technical field of thermal management of energy storage power stations, and discloses an immersion phase change and jet flow cooperative reinforcement thermal management system of an energy storage power station. An immersed phase-change cooling tank body of the system contains an energy storage battery pack and a low-boiling-point fluorinated liquid cooling liquid, so that the whole battery pack is immersed in the immersed phase-change cooling tank body; the condensation recovery device is connected with a steam outlet condensation vaporization medium; the liquid storage distribution unit comprises a main liquid storage tank and a special liquid storage tank, the main liquid storage tank is connected with the condensation recovery device, and the special liquid storage tank is connected with the bottom of the tank body through an electromagnetic drain valve; the multi-layer jet strengthening module comprises a top-layer annular jet pipeline, a bottom-layer annular jet pipeline and a middle-layer annular jet pipeline, the top-layer annular jet pipeline and the bottom-layer annular jet pipeline are connected with a main liquid storage tank and reflow through a circulating pump, and the middle-layer annular jet pipeline is connected with a special liquid storage tank driven by a high-pressure pump and provided with The temperature monitoring array acquires the real-time surface temperature of the battery pack in a distributed manner The dynamic control center is connected with all the modules. According to the system, efficient and uniform heat management of the energy storage battery pack is realized through cooperation of phase change and jet flow.

The invention provides a lithium ion battery core temperature prediction method based on a finite element model, and the method comprises the following steps: 1, designing an electrochemical test experiment, and constructing a one-dimensional electrochemical model containing a lithium ion battery electrochemical heat production mechanism; 2, designing a lithium ion battery temperature test experiment, obtaining electrochemical parameters, heat transfer characteristic parameters, internal thermophysical parameters and environmental parameters of the battery under different working conditions, and obtaining a temperature change curve of the center position and the surface of the battery; and step 3, based on the heat balance equation, establishing a three-dimensional heat transfer model having the same geometric characteristics as the battery used in the experiment. According to the experimental result in the step 2, the three-dimensional heat transfer model is subjected to non-uniform region division, each region corresponds to one one-dimensional electrochemical model, and the heat production rate per unit volume is calculated by the one-dimensional electrochemical model in the step 1; introducing the heat production rate of each area into a three-dimensional heat transfer model to calculate the temperature distribution of the battery, and designing an experiment to correct a one-dimensional electrochemical model; 4, modifying the operation conditions and heat dissipation conditions of the battery, and calculating and analyzing the temperature difference delta T between the center position and the surface position of the battery under different operation conditions and heat dissipation conditions by using the three-dimensional heat transfer model in the step 3; and 5, measuring the surface temperature of the battery, and calculating the temperature of the center of the battery according to the working condition of the battery in the step 4 and the delta T corresponding to the environment temperature, thereby realizing monitoring of the temperature of the center position of the battery. According to the method, a high-precision algorithm model is constructed and verified by utilizing data accumulated in an earlier-stage experiment, the central point temperature which is difficult to directly measure in the battery is predicted only through real-time and easily-acquired battery surface temperature information, operation condition parameters and heat dissipation conditions, key thermal state information is provided for a battery management system, and the battery management efficiency is improved. The method is used for real-time safety monitoring and thermal management optimization.

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 battery management systems, and discloses an intelligent battery management and safety control system and an electric flame gas stove. The system comprises a sensing engine for collecting battery multi-physics field data through a heterogeneous sensor array; the calculation engine is used for performing spatial-temporal feature extraction on the data to generate dynamic security boundary parameters; the analysis engine is used for analyzing the external power request and fusing the security boundary to generate a power distribution constraint set; the strategy generation engine is used for synchronously solving an optimal power output track and a thermal management control instruction in the constraint set; and the execution engine is used for executing power driving and heat dissipation adjustment. According to the system, accurate sensing of the internal state of the battery and early warning of the safety risk are achieved through the dynamic safety boundary, efficient and stable power output of the battery within the safety boundary is ensured through cooperative control of power and heat management, and the safety and energy efficiency of the whole system are improved.

The invention relates to an electric duct driving system integrated with a heat dissipation function and an aircraft, the aircraft comprises the electric duct driving system, the electric duct driving system comprises a casing, an electric driving assembly and a heat dissipation pipeline, a fan is arranged in the casing, and the electric driving assembly is in transmission connection with the fan and used for driving fan blades of the fan to rotate; the heat dissipation pipeline is arranged on the outer surface of the casing and provided with a cooling liquid inlet and a cooling liquid outlet, one part of the heat dissipation pipeline is connected to the outer surface of the casing, one end of the heat dissipation pipeline is connected to the cooling liquid outlet, and the other end of the heat dissipation pipeline is connected to the cooling liquid inlet, so that the electric duct driving system can utilize structural parts (namely the casing and the fan) of the electric duct driving system as components for heat dissipation; therefore, a heat management system does not need to be installed, the structure of the electric duct driving system is greatly simplified, the risks of system weight increment and part failure caused by the adoption of a centralized liquid cooling system are effectively reduced, the energy consumption of the whole machine is also effectively reduced, and the cruising ability of the aircraft is improved.

In a thermal management system for a vehicle and a method for controlling the same, the thermal management system includes a fluid transfer device configured to execute thermal management of at least one object, to be thermally managed, through introduced ambient air, and a controller configured to determine a target air flow rate required for thermal management of the at least one object to be thermally managed, and to control the fluid transfer device based on an optimal control value determined using a control model for a predictive state value according to a current state value and the target air flow rate.

The invention discloses a heat dissipation control method and device for a single-phase immersed liquid cooling charging pile and a medium, and relates to the technical field of battery thermal management, and the method comprises the steps: carrying out the high-precision scanning and dynamic feature extraction of a built-in fiber grating array of a cold plate according to a partition flow control signal, and obtaining a temperature field matrix and a dynamic thermal feature set; performing multi-dimensional fusion analysis and electrochemical coupling analysis on the temperature field matrix and the dynamic thermal feature set to generate a thermal coupling parameter set; performing real-time risk quantitative evaluation and risk topological mapping on the thermal coupling parameter set, and outputting a risk topological data set; and performing cooling intensity dynamic modulation according to the risk topology data set, and obtaining a partition flow redistribution instruction. According to the invention, fine monitoring of the cold plate-battery interface contact thermal resistance is realized through a high-precision pressure field reconstruction technology, the accuracy and reliability of pressure distribution detection are significantly improved, and the local overheating risk caused by an assembly gap is effectively eliminated.

The invention belongs to the technical field of electrochemical energy storage, and provides an immersed energy storage system and a thermal management method thereof, the immersed energy storage system comprises a sealed cabin, a battery module, an immersion liquid, a liquid cooling unit, a cooling liquid, a liquid cooling pipeline, a temperature sensor, an electrical device and a thermal management controller; the non-conductive immersion liquid with the conductivity smaller than 10 <-6 > S / m and the flash point larger than 200 DEG C is adopted to completely wrap the battery module, it is ensured that the energy storage battery cells are located in the same temperature physical environment, the temperature consistency of the system is greatly improved, the problem of uneven heat dissipation is fundamentally solved, the service life of the energy storage cabinet is directly prolonged, the immersion liquid has the flame-retardant characteristic, and the service life of the energy storage cabinet is prolonged. Thermal runaway of a battery cell can be effectively restrained, fire and explosion risks are reduced from the source, system operation safety is guaranteed, meanwhile, the type selection standard of cooling liquid is defined, the design of a sealed cabin is optimized, the heat exchange efficiency is improved through a double-circulation branch of a liquid cooling unit, the key bottleneck of an immersed cooling technology in energy storage system integration is thoroughly solved, and the energy storage system integration efficiency is improved. And full landing of technical advantages is realized.

The invention discloses a liquid cooling energy storage power station intelligent temperature control system based on DNN and fuzzy logic, and relates to the technical field of energy storage. Comprising a data acquisition and multi-dimensional preprocessing module used for acquiring liquid cooling energy storage multi-source working condition data in real time, performing feature extraction and performing data preprocessing; the DNN depth temperature prediction module is used for constructing a DNN depth temperature prediction model, predicting the temperature of the battery pack, identifying an overtemperature risk and taking safety guarantee measures; the fuzzy logic intelligent decision module is used for predicting the flow of the cooling liquid and implementing a temperature control regulation decision; and the execution and feedback self-optimization closed loop module is used for correcting the flow of the cooling liquid and realizing a self-learning evolution closed loop of temperature control regulation. The problems that an existing liquid cooling energy storage power station temperature control system is poor in non-linear and dynamic change adaptability, insufficient in temperature control precision and response speed and poor in energy consumption optimization, complex heat management requirements cannot be met, and then comprehensive operation performance is reduced are solved.