10607 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 relates to the technical field of battery thermal management, in particular to a battery thermal management control method and system, and the method comprises the steps: obtaining the basic operation parameter data of an automobile battery in real time, and carrying out the multi-dimensional data fusion, and obtaining a multi-dimensional data set; based on the thermodynamic model and the multi-dimensional data set, the temperature distribution condition in the battery is calculated in real time, and real-time temperature distribution information is obtained; based on the historical data and the operation state, the future temperature change trend of the battery is predicted through a recurrent neural network model; dynamically adjusting a control strategy of the battery thermal management system according to the real-time temperature distribution information and the prediction result; and analyzing the temperature difference condition of the battery monomers, detecting abnormal temperature rise, and performing temperature difference balance adjustment and triggering a multi-stage protection mechanism when the abnormal temperature rise exceeds a threshold value. According to the invention, the problems of inaccurate temperature prediction and response lag in the prior art are effectively solved, the control strategy is dynamically adjusted through real-time data fusion and recurrent neural network prediction, temperature difference balance and abnormal temperature rise detection are realized, the safety of the battery is improved, and the service life of the battery is prolonged.

The invention relates to the technical field of temperature regulation and control, in particular to a liquid cooling control method and system of a battery control device, in the liquid cooling control method and system, through real-time collection and area screening of temperature and power data, accurate recognition of a high-temperature area is achieved, a clear cooling requirement partition is provided, and the cooling requirement of a battery is met. A dynamic adjustment strategy of pressure and flow parameters of the liquid cooling pump is optimized through a genetic algorithm, the cooling response speed and control precision are improved while energy consumption and cooling efficiency are effectively balanced, the pump speed and the valve opening degree are adjusted in real time, temperature changes are rapidly responded through automatic control, gradual implementation of a cooling target is ensured, and the cooling efficiency is improved. The hysteresis in the heat management process is reduced, the temperature control effect is continuously evaluated through a fuzzy control algorithm, the cooling intensity is dynamically adjusted according to the monitoring result, efficient cooling is ensured, meanwhile, equalization of temperature distribution is achieved, and a systematic heat management framework is established through long-term data monitoring and continuous optimization of cooling operation. And efficient and stable operation of temperature management is realized.

The invention discloses a hydrogen fuel cell vehicle ultralow temperature cold start thermal management system, and relates to the technical field of hydrogen fuel cell vehicle thermal management, the hydrogen fuel cell vehicle ultralow temperature cold start thermal management system comprises a thermal management platform, the thermal management platform is in communication connection with the following modules: a temperature monitoring and predicting module, and the temperature prediction module is used for monitoring the temperature of key parts in the hydrogen fuel cell by using the temperature sensor and predicting the change trend of the temperature in the fuel cell in combination with the temperature prediction model. By utilizing the high-precision temperature sensor and the long-short-term memory network model, the internal temperature change trend of the fuel cell is pre-judged in advance, the heating power is dynamically adjusted, it is ensured that the temperature of the cell is rapidly increased to the proper working temperature in the ultralow-temperature environment, starting difficulty caused by local supercooling is avoided, the low-temperature starting time is remarkably shortened, and the starting efficiency is improved. The reliability and the stability of the system in an extreme environment are improved, and the normal operation of the hydrogen fuel cell vehicle in a cold region is guaranteed.

The invention discloses a dynamic control method of a lithium battery module intelligent equalization management system, and relates to the field of lithium battery module equalization, and the method comprises the steps: constructing a hierarchical data fusion platform, and generating a battery state data set containing SOC, SOH and an inconsistency evaluation value; a credibility reasoning algorithm is adopted to calculate a single body imbalance credibility factor value to divide an equalization stage, and equalization current is dynamically adjusted; a charge and discharge curve health factor is extracted through an LAB health factor algorithm, SOH is updated online in combination with extended Kalman filtering, and an SOH attenuation rate is fed back to the battery model; in-module equalization is carried out through a bidirectional energy transfer circuit, inter-module equalization is carried out through a ring bus topology, and layered topology linkage control is formed. The method has the advantages that the consistency and the heat management efficiency of the battery pack are improved through the hybrid equalization strategy and the layered topology linkage control, the service life of the battery pack is prolonged, and the overall performance and the safety of the electric vehicle are improved.

The invention relates to the technical field of new energy automobile thermal management, in particular to a direct cooling and heating management system and method in an automobile power battery. The method comprises the following steps: acquiring vehicle real-time operation condition data and battery pack state monitoring data; working condition mode recognition processing is conducted according to the vehicle real-time operation working condition data, and vehicle working condition mode feature data are generated; performing thermal load demand analysis on the battery pack state monitoring data based on the vehicle working condition mode characteristic data to obtain dynamic thermal load demand data of the battery pack; and according to the dynamic thermal load demand data of the battery pack, refrigerant demand quantity calculation and analysis are carried out, the refrigerant supply capacity of the current direct cooling system is evaluated, and refrigerant supply and demand matching feature data are obtained. The specific requirements of three heat sources of the battery, the motor and the cockpit for the refrigerant flow are quantified, and a refrigerant distribution strategy is formed according to the proportional relation, so that the safety of the battery is improved, and the driving comfort and the working stability of the electric driving system are also guaranteed.

The invention relates to the technical field of forklift power battery pack management, and discloses a forklift power battery pack management method, device and equipment and a storage medium and system, and the forklift power battery pack management system comprises a dynamic load prediction module, a multi-mode heat management module and a self-adaptive current control module. A dynamic load prediction model optimized through edge calculation is deeply coupled with a multi-mode thermal management system to form a real-time cooperative closed loop, and the problem of lagging of load change and battery temperature rise response is solved. And through closed-loop optimization of data streams among the modules, adaptive adjustment under multiple working conditions is realized, and the service life of the battery and the energy efficiency are remarkably improved under the hardware condition with limited resources. The mechanism of experimental calibration of cooling coefficient and real-time load coupling adjustment effectively balances cooling energy consumption and temperature control requirements, and significantly reduces system energy consumption. And meanwhile, the intelligent adaptability of the system is enhanced by long-term data recording and optimization iteration supported by the cloud platform, so that the system has the capability of continuously optimizing the performance in a complex operation environment.

The invention relates to the technical field of motor control, and discloses a brushless motor adaptive control method and system based on artificial intelligence, and the method comprises the steps: collecting the multi-point temperature data of a motor, building a thermal dynamic model, and reconstructing the complete temperature field distribution; identifying a relation function between motor parameters and temperature, and establishing a temperature sensitive parameter model; in combination with temperature field distribution and a temperature sensitive parameter model, learning long-term influence of control actions on temperature distribution, and predicting temperature evolution trends under different control strategies; constructing a multi-objective optimization control strategy, and generating a motor control instruction and a heat dissipation control instruction; dynamically selecting an optimal heat dissipation strategy combination according to the generated control instruction, the current working condition and the predicted heat influence; according to the invention, high-precision control and thermal management optimization of the brushless motor in a temperature change environment are realized.

The embodiment of the utility model provides a container, an energy storage device, an energy storage system and a charging network. The energy storage device comprises a container, a control module and a heat management module. The number of the containers is m, m is larger than or equal to 2, and the m containers are arranged in the first direction of the containers. In the first direction, the size of the container is smaller than that of a standard container. The container comprises a container body and a plurality of single batteries, and the plurality of single batteries are accommodated in the container body. And the control module is arranged in the box body and is used for electrically controlling the plurality of single batteries in the m containers. And the heat management module is arranged in the box body and is used for managing the temperature of the plurality of single batteries of the m containers. According to the energy storage device provided by the embodiment of the invention, the convenience in the transportation process of the container is improved, the transportation cost of the container and the energy storage device using the container is reduced, the space in the container can be fully utilized, the integration degree is high, and the assembly efficiency is improved.

The invention relates to the technical field of chip heat management, and discloses a chip heat distribution prediction modeling method and device, and the method comprises the steps: obtaining chip design information, carrying out the three-dimensional grid division through a pre-training transfer learning neural network, and constructing an electricity-heat-force multi-physics field coupling model; the method comprises the following steps: monitoring operation load data in real time, carrying out thermal simulation and generating a temperature distribution characteristic matrix, collecting data through a temperature sensor array, simulating thermal diffusion by using particle filtering and Bayesian inference, compressing and reconstructing the temperature distribution characteristic matrix by using a variational auto-encoder, generating a digital twinborn body, and optimizing a heat dissipation strategy by using deep reinforcement learning. The temperature control strategy is generated, the chip heat management precision is improved, the heat dissipation strategy is optimized, the performance and stability are improved, and the problem of insufficient prediction of temperature distribution in a traditional heat management scheme in the prior art is solved.

The invention provides a thermal runaway prevention and heat dissipation optimization method and system based on a capacitor module, and relates to the technical field of capacitor module thermal management, and the method comprises the steps: extracting the multi-source operation data features of a single capacitor through an improved layered visual attention network, carrying out the data complementation through combining a bidirectional probability diffusion model, and obtaining a multi-source operation data feature of the single capacitor; and discovering a causal relationship between network identification data by using a causal structure, generating a performance analysis report, constructing a spatio-temporal dynamic graph neural network to predict temperature field distribution, performing fault diagnosis and uncertainty quantification in combination with a multi-task learning framework, further constructing a layered early warning mechanism, and performing early warning based on a layered reinforcement learning framework. And a dynamic prediction map and a performance analysis report are combined, a heat dissipation strategy is optimized, cooperative control of the heat dissipation units is realized, an optimal heat dissipation scheme is finally obtained, thermal runaway is effectively prevented, and the safety and reliability of the capacitor module are improved.

The invention discloses an inverter intelligent control method based on a self-adaptive algorithm, and relates to the technical field of inverter intelligent control, and the method comprises the steps: multi-source temperature collection and environment recognition, machine learning-based electric-thermal coupling prediction, self-adaptive inverter parameter optimization, and cooperative thermal management and fault diagnosis self-repairing. According to the high-temperature or low-temperature failure risk of the motor and the inverter under the extreme climate, temperature distribution and load information are obtained in real time, the temperature rise trend is predicted in advance, and the current, voltage and modulation strategy of the inverter are actively adjusted, so that safe derating or torque compensation is achieved; multi-sensor cross validation and observer fusion are carried out when sensors drift or devices are aged, stable operation and efficient energy utilization of the system are kept, and the drivability and the whole vehicle reliability in an extreme environment are remarkably improved; in the process, fault diagnosis and self-repairing can be further improved through online model updating, and the durability and economical efficiency of the electric drive system are improved.

The invention relates to the technical field of power electronics, in particular to a photovoltaic off-grid inverter control method and system, and the method comprises the following steps: applying a test signal to identify an output interaction characteristic parameter, predicting the power generation power through combining with weather and attenuation, calculating the power fluctuation, and adjusting a current control parameter set. And calculating voltage and reactive power compensation parameters to generate an inverter control instruction, and combining a temperature load prediction trend to adjust a power allowable value to obtain a predictive power calibration coefficient. According to the invention, by analyzing the output interaction characteristics, enhancing the perception capability of the inverter to the actual operation environment, combining with the prediction of the photovoltaic power generation amount, realizing the prediction and influence evaluation of the power fluctuation, improving the adaptive adjustment capability of the current control parameters, improving the output voltage and reactive power control precision by utilizing the interaction characteristics, and optimizing the electric energy quality; and through thermal management of multi-point temperature and load prediction, the operation safety is improved, the service life of equipment is prolonged, and the operation performance of the photovoltaic off-grid system in a complex environment is improved.

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.

A heat management system includes: a first flow passage in which a reserve tank is not provided; a second flow passage in which a reserve tank is provided; a switching device configured to switch between coupling and uncoupling of the first flow passage and the second flow passage to and from each other; and a control device configured to control the switching device. The control device is configured to, when predetermined coupling conditions are met, make the heat medium flow through the first flow passage and the second flow passage that have been coupled to each other by the switching device. When the control device determines that air bubbles exceeding the allowable volume are present in the heat medium, the coupling conditions switch from being unmet to being met.

The invention relates to the technical field of energy storage management, in particular to a high-energy-density liquid cooling energy storage system based on thermal management optimization, which comprises a thermal response calculation module, a thermal risk area identification module, a cooling resource allocation module, a thermal decoupling state judgment module and a charging and discharging power limiting module. According to the method, the inlet temperature, the outlet temperature and the cooling liquid flow speed of the high-energy-density energy storage equipment are obtained, the unit thermal load conversion rate is calculated, the unit thermal response deviation degree is determined, the thermal risk area higher than the standard limit is clearly recognized in the energy storage equipment, the corresponding liquid cooling channel is accurately selected, and the cooling liquid pulse flow frequency is optimized; the pertinence and timeliness of the cooling liquid in actual use are effectively improved, the local overheating hidden danger is avoided, the lag response is marked in time by monitoring the cooling liquid pressure difference and the temperature rise change in real time, the decoupling state between the cooling liquid and the thermal load is judged, the charge and discharge power dynamic reduction measure is implemented, and the trend of abnormal and continuous accumulation of the local thermal load is restrained.

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 provides a lithium battery equalization thermal management method. Real-time temperature data is obtained by constructing a thermal distribution monitoring network, the temperature difference between a center and an edge area is analyzed, a thermal load distribution coefficient is calculated, and a dynamic heat dissipation intensity adjustment model is established; driving the multi-channel cooling system to operate according to the heat dissipation demand priority, and adjusting the flow distribution proportion of a cooling medium; a dynamic nonlinear feedback correction mechanism is adopted, secondary adjustment is carried out for uneven temperature distribution, and an optimal heat dissipation parameter combination is determined in combination with historical data. Uniformity control over temperature distribution of the battery module is achieved, the problem of heat accumulation in a center area is effectively solved, the heat dissipation efficiency under the rapid charging working condition is improved, and the safety performance and the service life of the battery module are guaranteed.

Systems, devices and methods for providing cooling to hardware components, and more specifically to manifold systems, devices and methods for thermal management of hardware in computer server racks and related equipment in computer data centers.

The invention discloses an automatic control method and device for a thermal management system of an electric vehicle, relates to the field of intelligent control, and realizes multi-step prediction of battery and motor heat production and thermal load change in the future by fusing external information such as a navigation path and weather forecast, plans a thermal management strategy in advance, and improves the response perspectiveness of the system. A multi-source disturbance dynamic structured correlation equalization technology is adopted, the coupling relation between heat sources is modeled, cross disturbance is compensated through a joint state function, and multi-heat-loop cooperative control is achieved. On the basis of a model predictive control (MPC) framework, temperature tracking errors and energy consumption penalty are optimized, the energy consumption of actuators such as a compressor and a water pump is reduced while a safe temperature interval is met, and the endurance is prolonged. And in combination with a state estimator fusion model and observation data, the control precision and robustness under a complex working condition are enhanced, and finally global optimal thermal management considering the service life of parts, the comfort of passengers and the energy efficiency is realized.

A thermal management method for metal solid-state hydrogen storage, a hydrogen fuel cell system thereof and a rail transit vehicle. The hydrogen fuel cell system comprises a hydrogen fuel cell module and solid-state hydrogen storage modules, which are communicated via a hydrogen pipe; a first branch is provided on the periphery of the hydrogen fuel cell module; a diverter valve is provided at a liquid outlet end of the first branch, one branch of the diverter valve being communicated with a heat dissipation system, and another branch of the diverter valve being communicated with a second branch. Using heat generated during power generation of a hydrogen fuel cell to successively start the solid-state hydrogen storage modules helps to increase the system starting speed, thus improving the efficiency of hydrogen fuel cell systems.

The invention relates to the technical field of electronic information, in particular to a multi-band cooperative interference gallium nitride phased-array antenna control method and system. The method comprises the steps of extracting key parameters of electromagnetic signals, and generating a cooperative interference strategy combination; mapping the frequency band optimization weight to a dynamic working mode of the gallium nitride power amplifier unit, adjusting the radiation pattern characteristics of the reconfigurable dipole array according to the power distribution parameters, and constructing a composite beam forming framework; phase weighting and spatial multiplexing are carried out on the interference signals of all the frequency bands based on the composite beam forming architecture, and a multi-beam interference cluster is generated; thermodynamic state data of the gallium nitride power amplifier module in the multi-beam interference cluster generation process are collected in real time, and heat dissipation parameters of the liquid cooling system are regulated and controlled according to the thermodynamic state data. Intelligent collaboration and accurate pointing of multi-band interference signals are realized, the interference coverage range and the energy utilization rate are improved, and an efficient interference system integrating electromagnetic sensing, multi-beam collaboration and thermal management is formed.

The invention discloses a heat dissipation optimization method and system for a power device based on heat flow path reconstruction, and aims to improve the heat dissipation efficiency of the power device in the working process and reduce the adverse effect of thermal stress on the performance and service life of the device. The method comprises the following steps: firstly, acquiring real-time temperature field distribution data of a target power module during the working period of a power device, and determining an initial heat flow path of the module based on the data; performing heat sensitivity analysis on each component in the target power module; identifying a heat flow shielding area according to the heat sensitive data, and reconstructing the initial heat flow path on this basis to generate an optimized heat flow path; and finally, an efficient heat dissipation channel is constructed according to the optimized heat flow path, so that effective heat dissipation optimization of the power device is realized. The method can dynamically identify the thermal bottleneck and actively optimize the heat dissipation path, is suitable for thermal management design of high-power-density electronic equipment, and has high engineering practical value.

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 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 utility model relates to a spraying type heat pipe structure and a heat management system.The spraying type heat pipe structure comprises an evaporation section, a condensation section, a liquid pump and a spraying pipe set, the evaporation section communicates with the condensation section, the liquid pump and the spraying pipe set are both arranged in the evaporation section, a power element and a liquid working medium are arranged in the evaporation section, and the liquid pump communicates with the spraying pipe set; and the liquid pump can spray the liquid working medium to the surface of the corresponding power element through the spraying pipe group, so that the liquid working medium can absorb heat, be gasified and enter the condensation section. According to the spraying type heat pipe structure and the heat management system provided by the invention, the problem that an existing cooling mode is difficult to meet the increasing heat dissipation requirement of a power element is solved.

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 provides a wide-voltage self-adaptive closed-loop vector swimming pool pump anti-interference method, and relates to the technical field of motor control and power electronics, and the method comprises the steps: collecting three-phase power supply voltage fluctuation characteristic parameters and motor operation state parameters in real time; performing amplitude compensation and phase synchronization correction on the voltage parameter based on the dynamic voltage compensation factor; a closed-loop vector anti-interference control model is constructed, and model parameters are adjusted in real time through a vector immunity coefficient; dynamically correcting control output by adopting a multivariable feedback regulation mechanism; executing an anti-interference instruction and synchronously updating PWM modulation parameters, and verifying a control effect in combination with hardware-in-the-loop simulation; and parameter self-learning optimization is realized through a genetic algorithm. The dynamic anti-interference capability under power grid voltage fluctuation and harmonic interference is improved, intelligent thermal management is realized through a temperature-voltage-current multi-dimensional coupling model, full-life-cycle self-adaptive optimization of the system is guaranteed, and the problems of compensation lag, insufficient harmonic suppression and poor long-term stability are effectively solved.

The invention discloses a polylactic acid injection molding mold based on a gradient heat conduction composite structure and a heat management method thereof, and belongs to the technical field of high polymer material molding processing equipment.The polylactic acid injection molding mold comprises a) a surface high heat conduction layer which is made of a copper-based composite material, has the heat conduction coefficient larger than or equal to 400 W / m.K and is used for rapidly and directionally transferring heat to the surface of a mold cavity; and b) an intermediate transition layer composed of a titanium alloy porous structure. High-efficiency production is realized through innovative design and advanced technology. Integrated metallurgical bonding of the gradient heat conduction structure is achieved through the selective laser melting technology, and the heat flow directivity is enhanced; the dual-mode cooling system is combined with closed-loop temperature control, and the temperature is accurately regulated and controlled; the high-performance material improves the comprehensive performance of the mold; and the structural stability is guaranteed through accurate technological parameters. According to the thermal management method, through multi-physical field simulation optimization, rapid heating and cooling are achieved, the forming period is shortened to 16-18 seconds, the calculation efficiency is improved by 80%, and the production efficiency and the product quality are effectively improved.

The invention relates to a temperature control technology of an energy storage system, and discloses a temperature control system and method of a lithium ion battery energy storage system, which can realize accurate temperature control, reduce the power consumption of temperature control and reliably guarantee high-efficiency and long-life operation of the lithium ion battery energy storage system. The temperature control system comprises a battery management system, a heat management system and a battery temperature sampling unit, the battery temperature sampling unit is used for sampling the temperature of each battery cell in the energy storage system in real time; the battery management system is used for generating a temperature control strategy according to a preset temperature feature point in combination with the current temperature data of the battery cell and the current working state of the energy storage system, and issuing the temperature control strategy to the thermal management system; the temperature characteristic point is preset according to characteristic data of a battery cell used in the energy storage system; and the heat management system is used for controlling the temperature of the energy storage system by executing a temperature control strategy. The method is suitable for the energy storage system.