208 results about "Thermal network" patented technology

The invention discloses a permanent magnet synchronous motor temperature monitoring method based on digital-analog hybrid drive, and the method specifically comprises the steps: dividing a motor into a plurality of heat source nodes, including a stator winding, a stator tooth part, a rotor core and the like, connecting the nodes through a thermal resistance and thermal capacity network, building a thermal network model of the motor, and carrying out the thermal network model; calculating the initial values of thermal resistance and thermal capacity of each component of the motor, and optimizing parameters in a thermal network model by using a differential evolution algorithm based on the lumped parameter thermal network model and in combination with a data-driven strategy. Furthermore, temperature rise prediction is dynamically adjusted according to motor state data (such as stator current, rotating speed and the like) collected in real time so as to realize real-time temperature estimation. The method is high in temperature estimation precision, does not affect the performance of the motor, is simple in calculation, is good in real-time performance, and has physical interpretability. The temperature rise of the motor can be predicted in real time under different working conditions, early warning is given out, motor faults caused by too high temperature rise are effectively avoided, and the reliability and safety of the motor are improved.

The invention discloses a quick response flexible temperature sensor with low thermal crosstalk and a preparation method thereof. The sensor comprises a contact layer, a sensing layer, an electrode layer and a substrate layer, wherein the contact layer comprises a heat conduction layer and a heat insulation network; the heat-conducting layer is made of a heat-conducting composite material and comprises polydimethylsiloxane and flake carbon powder; the heat insulation network and the substrate layer are made of a heat insulation composite material which comprises polydimethylsiloxane and hollow glass microspheres; the sensing layer comprises a plurality of sensing units arranged in an array, the sensing units are connected with the electrode layer and output resistance signals, the heat conduction layer and the substrate layer are arranged over and under the sensing units respectively, and the heat conduction and heat insulation synergistic structure can enhance the quick response of the sensing units to the temperature; a thermal insulation network is embedded in the contact layer to block thermal crosstalk between adjacent sensing units. The temperature sensor has the advantages of quick response, low thermal crosstalk and high reliability in a wide range, and large-scale production and preparation can be realized.

The invention discloses a synchronous reluctance motor magnetothermal coupling rapid calculation method based on a dynamic thermal network, and belongs to the technical field of motors. Comprising the following steps: calculating motor loss by adopting a finite element electromagnetic field model, and calculating a convective heat transfer coefficient by adopting a finite element fluid field model; constructing a three-dimensional thermal network comprising conduction, contact, convection thermal resistance, thermal capacity and a heat source, and solving to obtain an average temperature and a boundary temperature of component nodes; constructing a sub-domain temperature field calculation model of the heat source component, and calculating temperature distribution in combination with boundary conditions; introducing average temperature compensation thermal resistance and carrying out dynamic correction; carrying out magnetothermal coupling iteration, and updating the loss and the temperature until the precision is met; and introducing maximum temperature compensation thermal resistance into the thermal network, and solving to obtain an average temperature and a maximum temperature transient temperature rise curve of each component. Based on the technical means of combining electromagnetic field and fluid field finite element simulation with thermal network and subdomain temperature field calculation, efficient calculation of magnetothermal coupling of the synchronous reluctance motor is achieved.

The invention relates to the technical field of boiler control, in particular to a multivariable coupling thermal process regulation and control system and method for carbon pollution governing, and the method comprises the steps: collecting multi-source data such as acoustic emission, temperature, humidity and spectrum, and constructing a feature sequence through time mark alignment and wavelet packet enhancement; a heat value characterization quantity is predicted by using a Shenchang differential equation model fused with dynamic gating, a partition equivalent thermal network model is driven on this basis, and accurate prediction of a future time domain temperature field is realized by dynamically correcting thermal resistance and thermal capacity; based on the prediction result, a control instruction is solved through multi-objective optimization under the condition that the active temperature constraint is met; and in combination with heat flow density feedback, a layered reinforcement learning controller is adopted for online compensation of a pre-feedback instruction, and stable and efficient regulation and control of the boiler are achieved.

The invention provides an IGBT junction temperature prediction model construction method and system, and relates to the technical field of power electronic device thermal management, and the method comprises the steps: obtaining an initial data set representing the transient thermal response relation between an IGBT chip and an NTC temperature measurement point in an IGBT power module where the IGBT chip is located; training a neural network model based on the initial data set, and learning and representing a nonlinear function relationship between time and thermal impedance; inputting a preset new time sequence into the trained neural network model, and generating a time-continuous and noise-suppressed optimized thermal impedance data set; and based on the data set, performing parameter fitting on a preset lumped parameter thermal network model to identify thermal resistance and thermal capacity parameters of the model so as to complete construction of the junction temperature prediction model. According to the method, the neural network is used as a data optimization tool in a physical model parameter identification process, and accurate and convenient online prediction of the IGBT junction temperature is realized only by using the temperature signal of the NTC temperature measurement point of the module.

The invention relates to the technical field of intelligent heat supply management, in particular to an intelligent heat supply integrated management system based on multi-source data driving, which comprises a multi-source data acquisition module for acquiring multi-source data of each target heat supply area of a heat supply network; the key delay time extraction module is used for acquiring the adjustment condition of the heat supply control data to generate key delay time; the sensitive parameter identification module is used for determining a heat supply adjustment sensitive parameter and a heat supply response sensitive parameter based on the key delay time; the characteristic interval analysis module is used for determining a change trend characteristic interval based on a pre-change trend corresponding to the change characteristic interval; the pre-adjustment time determining module is used for determining a plurality of pre-adjustment times based on the change trend characteristic interval; and the pre-adjustment time calling module is used for acquiring the real-time multi-source data of the heat supply network to determine whether pre-adjustment is started or not, and determining the pre-adjustment time. The response speed and the adjusting precision of the heat supply system are improved.

Disclosed is a method for constructing an optimal scheduling model of an integrated energy system considering virtual thermal storage, which relates to the technical field of electric power systems. The method includes: establishing an operation model of an apparatus, a demand response model of an energy load, a charging model of an electric vehicle, and an energy flow model of a heat supply network of the virtual thermal storage in the integrated energy system; processing, according to a second-order cone relaxation method, a direct current power flow model of a power distribution network, and constructing the optimal scheduling model of the integrated energy system by taking minimization of total cost of an energy operator as an objective, thereby coordinately and optimally scheduling a plurality of energy sources.

The invention relates to a heat exchange network transformation method and device. The method comprises the steps that a heat exchange network topological structure is constructed; continuously updating model parameters of the basic model of each heat exchange device based on the time sequence data to obtain updated model parameters of each time period in the plurality of time periods; calculating evaluation indexes of the heat exchange devices according to the updated model parameters, and comprehensively sorting all the heat exchange devices based on the evaluation indexes to obtain a sorting result; target time periods in typical working conditions are determined from the multiple time periods, and heat exchange equipment to be transformed is screened out from all the heat exchange equipment on the basis of the sorting result of the target time periods; solving the constructed optimization problem to obtain a transformation scheme of the heat exchange equipment to be transformed; the optimization problem takes the increase amplitude of the heat exchange area of the heat exchange equipment to be transformed as an optimization variable, and takes the minimum total annual cost as an optimization target, so that the dependence on artificial experience can be reduced, and the transformation scheme generation efficiency is improved.

The invention relates to the technical field of high-power high-voltage frequency converters, and discloses a high-voltage frequency converter IGBT module junction temperature monitoring method, which comprises the steps of constructing an electrothermal coupling model by adopting a Foster type equivalent thermal network based on electrical characteristics and structural parameters of an IGBT module; based on the electrothermal coupling model, simulation is carried out under different operation conditions, junction temperature data of multiple groups of IGBT modules and corresponding electrical data are obtained, and a training sample set is constructed; constructing a long-short-term memory recurrent neural network based on a macro-micro attention mechanism, and training by using the training sample set to obtain an IGBT module junction temperature monitoring model; and inputting real-time electrical data by using the trained IGBT module junction temperature monitoring model, and outputting an IGBT junction temperature monitoring value. According to the method, the generalization and engineering applicability of the model are improved while the junction temperature monitoring precision is ensured.

The present invention relates to an energy system (1) and a method for operating the energy system (1), which comprises a hydrogen production unit (2) with at least one electrolyzer (3) for water electrolysis thermally coupled to a cooling water circuit (4), and a heat pump (5) whose heat source side (6) is thermally coupled to the cooling water circuit (4) and whose heat sink side (7) is connected to a district or commercial heating circuit (10) via a heat exchanger (8). According to the invention, a heat storage device (9) is provided in the district or commercial heating circuit (10), whose return line (11) is connected after the heat exchanger (8) and whose feed line (12) is connected before the heat exchanger (8) of the heat pump (5), so that the return temperature of the district or commercial heating circuit (10) is increased by heat from the heat storage device (9).

The application provides a kind of IGBT junction temperature prediction model construction method and system, it is related to power electronic device thermal management technical field, method includes: obtaining the initial data set of the transient thermal response relationship between the IGBT chip and the NTC temperature measuring point in the IGBT power module;Based on the initial data set, the neural network model is trained, and the nonlinear function relationship between time and thermal impedance is learned and characterized;The preset new time series is input into the trained neural network model, and the optimized thermal impedance data set with continuous time and noise suppression is generated;Based on the data set, the lumped parameter thermal network model is parameter fitted, to identify its thermal resistance and heat capacity parameters, complete the construction of junction temperature prediction model.The application uses neural network as a data optimization tool in the parameter identification process of physical model, only uses the temperature signal of NTC temperature measuring point provided by the module, realizes the accurate, convenient online prediction of IGBT junction temperature.

The invention relates to a lithium battery module temperature estimation method based on a multi-state electrothermal coupling model, and relates to the technical field of lithium battery temperature state estimation. Constructing a multi-state electrothermal coupling model of the single battery, wherein the multi-state electrothermal coupling model comprises an RC second-order equivalent circuit model and a multi-state equivalent thermal network thermal model; constructing a hierarchical integrated multi-state electrothermal coupling model of the battery module by connecting each single electric model in series and additionally arranging a conductive thermal resistor between each single electric model to describe heat exchange between adjacent batteries; performing parameter identification on the integrated model by adopting an improved overall cluster optimization algorithm; and based on the model after parameter identification, combining an adaptive unscented Kalman filter which dynamically adjusts noise covariance by adopting an exponential weighted moving average algorithm, and carrying out real-time estimation on the internal and surface temperature states of the battery module. According to the method, the temperature estimation precision and the long-term operation robustness of the battery module under the complex working condition are remarkably improved through the steps.

The invention belongs to the technical field of polymer composite materials, and relates to a light-weight, high-heat-conductivity and flame-retardant composite material for a new energy automobile air conditioning system and a preparation method of the light-weight, high-heat-conductivity and flame-retardant composite material. 10 to 25 parts of multifunctional compound filler; the multifunctional compound filler is formed by compounding two-dimensional titanium carbide nanosheets and hexagonal boron nitride microsheets according to the mass ratio of (1: 4)-(1: 1). 2 to 5 parts of compatilizer; 0.1 to 0.5 part of an antioxidant; and 0.5 to 1.5 parts of a lubricant. Through precise compounding of MXene and h-BN, a new triple synergistic mechanism of heat conduction, electromagnetic shielding and flame retardance is created, hexagonal boron nitride serves as a main heat conduction phase, and a phonon conduction path is built in a matrix through a sheet structure of the hexagonal boron nitride; the two-dimensional titanium carbide nanosheets play a bridging role among the h-BN micron sheets by virtue of high conductivity and huge specific surface area, so that the interface thermal resistance is remarkably reduced, a heat-conducting network is optimized, and meanwhile, the metal conductivity of MXene endows the material with excellent electromagnetic shielding effectiveness.

The invention provides an interface thermal resistance testing method and testing device, and belongs to the technical field of semiconductor device testing. The test method comprises the following steps: acquiring an actual cumulative structure function curve of a plurality of contrast samples of the semiconductor device, constructing a thermal structure model of the semiconductor device, and establishing a thermal network model corresponding to the thermal structure model, the thermal network model is used for representing an equivalent thermal structure of a heat flow path of the semiconductor device from a heating junction to an environmental medium; optimizing the parameters of the thermal network model through the actual cumulative structure function of each contrast sample; and obtaining the thermal resistance value of each interface in the semiconductor device according to the optimized thermal network model. The thermal resistance of different interfaces in the semiconductor device can be determined.

The invention discloses an IGBT aging monitoring method and apparatus, and an electronic device. The method comprises the steps of obtaining a pre-established first junction temperature expression, a first shell temperature expression and a model parameter conversion model of a to-be-monitored IGBT; the actually measured junction temperature and the actually measured shell temperature of the IGBT to be monitored and initial values of model parameters of the four-order Cauer thermal network model are obtained; fitting the first junction temperature expression in combination with the actually measured junction temperature to obtain a junction temperature initial value coefficient and a time constant; inputting different values of the junction temperature initial value coefficient, the time constant and the model parameter into a model parameter conversion model to obtain a shell temperature initial value coefficient corresponding to each value; inputting each value of the model parameter and the initial value coefficient of the shell temperature into a first shell temperature expression to obtain the shell temperature corresponding to each value; and evaluating the aging state of the to-be-monitored IGBT according to the model parameter corresponding to the shell temperature closest to the actually measured shell temperature. According to the invention, the aging state can be accurately evaluated in real time in different states.

A transmission system bearing interface modeling method includes the steps of: establishing a three-dimensional (3D) model of a bearing interface, and performing grid generation for a fluid domain of the bearing interface within the 3D model; determining simulation operating conditions, modeling the fluid domain using a volume of fluid (VOF) model, and capturing phase interfaces in multiphase flow within a gear transmission; modeling a solid domain of the bearing interface using a thermal network model, and discretizing the solid domain into a plurality of temperature nodes; calculating frictional heat generation of a gear pair to obtain heat sources under meshing conditions, and applying the heat sources to the thermal network model for simulation; and packaging the modeled bearing interface into an analysis system to calculate a heat source of the bearing interface. Reference can be provided for temperature variation and multiphase flow behavior in gear transmissions, improving research efficiency.

The invention provides a heat-resistant efficient flame-retardant TPU composite material and a preparation method thereof. The formula of the composite material comprises polyether type TPU, polycarbonate type TPU, a halogen-free flame retardant, a multifunctional additive MXene-PU, CNT-NH2, a dispersant, an antioxidant and a lubricant. According to the composite material disclosed by the invention, polyether type TPU and poly-carbon type TPU are blended to balance heat resistance and flexibility, the surfaces of MXene nanosheets are grafted with polyurethane with polyether and poly-carbon chain segments to obtain MXene-PU, the compatibility of the polyether type TPU and the poly-carbon type TPU is improved, and meanwhile, through construction of an electric conduction and heat conduction network of MXene and CNT, efficient heat-resistant and antistatic synergistic effects are exerted. Due to the excellent synergistic flame-retardant effect of the poly-carbon TPU, the carbon nanotubes and the MXene, the dosage of a flame retardant is greatly reduced, and the flame-retardant efficiency is improved. The heat-resistant efficient flame-retardant TPU composite material has excellent heat-resistant, flame-retardant and antistatic properties, and has a wide application prospect in the fields of cables and the like.

The invention discloses a parameter transformation method of an equivalent thermal network model and a related device, and the method comprises the steps: obtaining the complex frequency domain network impedance of a Foster thermal network model through curve fitting; according to the complex frequency domain network impedance of the Foster thermal network model, all thermal parameters in the Cauer model are solved in an admittance solving mode, and the thermal parameters of the Cauer model can be obtained through thermal parameter transformation of the Foster model by means of the method and the related device.

This invention discloses a method and system for cross-cycle waste heat utilization in chemical industries, comprising multi-layer energy storage units. The method includes: acquiring flow parameters of a chemical system in multiple single cycles; formulating energy targets and energy consumption requirements for the chemical system based on these parameters; calculating the heat exchange network structure of the chemical system within each single cycle based on the energy targets and energy consumption requirements; integrating the heat exchange network structure and energy targets within each single cycle; and designing the installation locations of the multi-layer energy storage units in the chemical system based on the integrated heat exchange network structure and energy targets to achieve cross-cycle waste heat energy recovery and utilization. This invention solves the problem of existing technologies' inefficient utilization of chemical waste heat from different cycles, leading to significant heat energy waste and low energy utilization efficiency in chemical systems.

The invention discloses a three-phase copper bar temperature estimation method and system of a new energy automobile electric drive system, and relates to the technical field of electric automobile electric drive, and the method comprises the steps: obtaining the vehicle environment temperature and the vehicle time, and recording the time point during dormancy, the three-phase copper bar environment temperature and the three-phase copper bar estimation temperature; reading the time point when the vehicle is awakened after the dormancy, and determining the dormancy time of the vehicle by combining the dormancy time point; according to the current vehicle environment temperature, the vehicle dormancy time, the three-phase copper bar environment temperature and the three-phase copper bar estimated temperature, through a pre-constructed four-dimensional temperature estimation table when the three-phase current is zero, the initial temperature of the three-phase copper bar after waking up is obtained through table look-up; and according to the current environment temperature of the vehicle and the initial temperature of the awakened three-phase copper bar, the current temperature of the three-phase copper bar is calculated through a pre-established thermal network model from the environment temperature to the temperature of the three-phase copper bar. The method can achieve the accurate estimation of the temperature of the three copper bars, and effectively balances the performance and safety of an electric drive system.

The application discloses a kind of multi-energy collaborative heating system risk assessment and regulation method and device, based on improved GNOME model, risk source in multi-energy collaborative heating system is analogized as oil spill source, risk propagation is analogized as oil spill diffusion, by defining risk particle and giving its risk type, risk level, initial position and influence range etc. Property, using similar convection and diffusion mechanism in oil spill model, in combination with energy flow and information transmission in heating system and other factors, the propagation path and change of risk in heating network are simulated. The present application helps to master the risk development trend in real time, early warning potential risks, provides strong support for formulating targeted risk control measures, and ensures the safe, stable and efficient operation of multi-energy collaborative heating system.

This invention discloses a method for IGBT temperature equalization control in parallel DC / DC converters of DC microgrids, belonging to the field of IGBT active temperature equalization control technology. The method includes nine steps: IGBT power loss calculation, IGBT thermal network model establishment, IGBT thermoelectric coupling model construction, IGBT junction temperature calculation in the DC / DC converter, average IGBT junction temperature calculation in the parallel DC / DC converter, calculation of the difference between the IGBT junction temperature and the average junction temperature in the parallel DC / DC converter, calculation of the virtual impedance for IGBT temperature equalization fine-tuning, adding the virtual impedance to the droop control loop, and generating PWM drive signals for the parallel DC / DC converter based on voltage and current dual closed-loop control. This invention adds the virtual impedance for IGBT temperature equalization fine-tuning to the traditional droop control, adjusting the current flowing through the IGBTs in each DC / DC converter, so that the IGBT junction temperatures in each parallel DC / DC converter tend to be uniform, thereby improving the overall system reliability.

According to the wind turbine generator blade icing dynamic early warning system provided by the invention, through omnibearing monitoring of the frequency modulation continuous wave radar group, the orthogonal weaving piezoelectric fiber array and the infrared temperature measurement unit, airspace water drop distribution, blade vibration characteristics and multi-dimensional dynamic changes of a surface temperature field are accurately captured; by combining improved Kalman filtering, wavelet transformation and a dynamic weight distribution algorithm of an intelligent decision module, traditional single threshold judgment is upgraded to comprehensive threat index deduction based on digital twinborn bodies, and the temporal-spatial resolution and reliability of icing threat assessment are remarkably improved; the execution control module achieves heating network partition accurate regulation and control and unit operation state collaborative optimization according to the generated anti-icing strategy, energy waste of traditional global heating is avoided, material damage caused by local overheating or underheating is effectively restrained, finally, anti-icing energy consumption is reduced under the complex meteorological condition, and the anti-icing efficiency is improved. And meanwhile, the power generation efficiency loss of the unit under the icing working condition is greatly reduced.

The application belongs to the technical field of high-power liquid-cooled charging pile heat management. A liquid-cooled super-charging pile all-weather efficient heat management system based on superconducting heat pipe and heat pump circulation comprises a liquid-cooled super-charging pile core heating unit, a liquid-cooled circulation loop, a control unit, a superconducting heat pipe heat exchange network, a heat pump circulation unit capable of bidirectional switching of working conditions, and an environment-side heat exchange unit. The phase change heat exchange end of the superconducting heat pipe heat exchange network is thermally coupled with the liquid-cooled super-charging pile core heating unit and the liquid-cooled circulation loop throughout the process. The heat collecting / cold collecting end of the superconducting heat pipe heat exchange network is integrated with the first heat exchange end of the heat pump circulation unit capable of bidirectional switching of working conditions. The second heat exchange end of the heat pump circulation unit capable of bidirectional switching of working conditions is coupled with the environment-side heat exchange unit. The system can stably operate in an extreme wide temperature range of -40 DEG C to 55 DEG C, has a prolonged service life, and has a remarkable energy-saving effect.

This invention relates to a solid-state hydrogen storage tank and its preparation and filling / discharging methods, belonging to the field of hydrogen storage and transportation technology. It solves the technical problem that the low thermal conductivity of granular and powdered hydrogen storage alloys leads to reduced hydrogen absorption and discharging rates, while existing solid-state hydrogen storage tanks with internal heat exchange structures suffer from complex manufacturing processes and high costs. A solid-state hydrogen storage tank includes a valve, a tank body, a metal mesh array, and granular hydrogen storage alloy dispersedly filled within the metal mesh array. The tank body is a cylindrical, straight-sided bottle shape. The valve fits into the bottle opening of the tank body. The metal mesh array is densely filled inside the tank body and tightly adheres to the inner wall of the tank body. The solid-state hydrogen storage tank of this invention constructs a metal mesh array through the combination of single metal mesh tubes, forming a dense and continuous metal mesh heat transfer network with high thermal conductivity. This reduces the high / low temperature levels of the hydrogen storage alloy bed, especially in the core area, and significantly shortens the hydrogen filling time.

The invention discloses a time-varying thermal failure probability estimation method and system for a deep groove ball bearing, and belongs to the field of bearing design. The method comprises the following steps: constructing a basic parameter model containing a mixed random parameter vector and a limit state function; establishing a transient thermal network model to calculate time-varying temperature response; constructing an agent model to replace high-time-consumption heat generation rate calculation; a self-adaptive time node sampling strategy is adopted, a proxy model and a thermal network model are combined to process large-scale samples, and the time-varying thermal failure probability is estimated. The system comprises a basic parameter modeling module, a transient thermal network simulation module, an agent model construction module and a self-adaptive probability evaluation module which correspond to the system. According to the method, the time-varying and random dual uncertainty is fused, and the proxy model and the adaptive sampling strategy are utilized, so that the defects of conservative property of a traditional static evaluation method and low efficiency of a traditional probability simulation method are effectively overcome, and accurate evaluation of the thermal behavior of the bearing under the dynamic working condition and remarkable improvement of probability calculation efficiency are realized.

The application discloses a kind of EKF-based photovoltaic inverter IGBT thermal network online parameter identification method, comprising the following steps: S1, using third-order Cauer network, the heat transfer path of IGBT module establishes IGBT thermal network discrete state space model;S2, based on IGBT thermal network discrete state space model, design EKF algorithm for thermal parameter joint estimation for the synchronous estimation of state and parameter;S3, using current sensor and voltage sensor real-time acquisition IGBT current waveform, voltage waveform, and preprocessing;S4, in the embedded microcontroller of photovoltaic inverter, with fixed sampling period, EKF algorithm is operated, time update and measurement update are sequentially executed in each cycle, and the optimal estimation value of current time updated thermal parameter and junction temperature estimation value are output.The application can track the actual thermal characteristics of IGBT in real time, solve the parameter mismatch problem, and realize dynamic online identification of thermal parameters.

This application relates to a method and system for IGBT hotspot identification based on transient thermal resistance curves, belonging to the field of IGBT thermal monitoring technology. The method includes: loading the junction-shell transient thermal resistance curve from the datasheet to construct a fractional-order thermal network model containing equivalent thermal resistance, thermal capacity, and fractional order; obtaining model parameters through parameter identification; real-time acquisition of electrical quantities and temperature to calculate power loss; substituting the power loss into the fractional-order differential equation to solve for the junction-shell temperature difference, and combining this with the operating temperature to obtain a real-time estimated junction temperature; and identifying hotspots based on the estimated junction temperature to obtain hotspot status information. This method achieves a complete closed loop from offline modeling and parameter identification to real-time junction temperature monitoring and hotspot identification. This application solves the problems of low reliability of a single junction temperature criterion and the inability to distinguish the location of thermal aging in the chip layer, solder layer, and substrate layer in IGBT thermal monitoring.

The invention discloses a hybrid thermal network modeling method and system for a journal sticking type synchronous generator, and belongs to the technical field of electrical excitation synchronous generator thermal network modeling analysis, and the method comprises the steps: dividing the journal sticking type synchronous generator into a solid heat transfer domain and a fluid heat transfer domain, and carrying out the node discretization of each region; establishing thermal resistance connection among the discrete nodes, and constructing a thermal network model comprising conduction thermal resistance, contact thermal resistance and initial convection heat transfer thermal resistance; setting a characteristic fluid heat transfer subdomain physical boundary condition, carrying out local three-dimensional steady-state fluid dynamic simulation, carrying out inversion calculation to extract a convective heat transfer coefficient, and correcting convective heat resistance of a corresponding node in the heat network model; and on the basis of the corrected thermal network model and the physical attributes of the nodes, establishing a global thermal balance differential equation set, and solving the global thermal balance differential equation set by adopting a temperature-loss coupling iteration method to obtain global steady-state temperature field data. The thermal management design precision and efficiency of the generator can be improved.

The present application relates to a kind of life prediction method and system considering IGBT module bonding wire failure.The method includes determining the health state of IGBT module according to the online monitoring data of IGBT module;Online monitoring data includes: the number of broken bonding wire;When IGBT module is healthy module, directly obtain transient impedance curve, and determine RC thermal network model according to transient impedance curve, and then carry out power cycle experiment, realize life prediction;When IGBT module is aging module, according to the transient thermal impedance measurement test measured IGBT module current transient thermal impedance curve, and determine the current RC thermal network model using current transient thermal impedance curve, and then carry out power cycle experiment, realize life prediction.The present application can improve the accuracy of life prediction result of IGBT module.