• Title/Summary/Keyword: Thermal Network

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Modeling and Thermal Characteristic Simulation of Power Semiconductor Device (IGBT) (전력용 반도체소자(IGBT)의 모델링에 의한 열적특성 시뮬레이션)

  • 서영수;백동현;조문택
    • Fire Science and Engineering
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    • v.10 no.2
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    • pp.28-39
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    • 1996
  • A recently developed electro-thermal simulation methodology is used to analyze the behavior of a PWM(Pulse-Width-Modulated) voltage source inverter which uses IGBT(Insulated Gate Bipolar Transistor) as the switching devices. In the electro-thermal network simulation methdology, the simulator solves for the temperature distribution within the power semiconductor devices(IGBT electro-thermal model), control logic circuitry, the IGBT gate drivers, the thermal network component models for the power silicon chips, package, and heat sinks as well as the current and voltage within the electrical network. The thermal network describes the flow of heat form the chip surface through the package and heat sink and thus determines the evolution of the chip surface temperature used by the power semiconductor device models. The thermal component model for the device silicon chip, packages, and heat sink are developed by discretizing the nonlinear heat diffusion equation and are represented in component from so that the thermal component models for various package and heat sink can be readily connected to on another to form the thermal network.

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Thermal Analysis of Water Cooled ISG Based on a Thermal Equivalent Circuit Network

  • Kim, Kyu-Seob;Lee, Byeong-Hwa;Jung, Jae-Woo;Hong, Jung-Pyo
    • Journal of Electrical Engineering and Technology
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    • v.9 no.3
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    • pp.893-898
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    • 2014
  • Recently, the interior permanent synchronous motor (IPMSM) has been applied to an integrated starter and generator (ISG) for hybrid electric vehicles. In the design of such a motor, thermal analysis is necessary to maximize the power density because the loss is proportional to the power of a motor. Therefore, a cooling device as a heat sink is required internally. Generally, a cooling system designed with a water jacket structure is widely used for electric motors because it has advantages of simple structure and cooling effectiveness. An effective approach to analyze an electric machine with a water jacket is a thermal equivalent network. This network is composed of thermal resistance, a heat source, and thermal capacitance that consider the conduction, convection, and radiation. In particular, modeling of the cooling channel in a network is challenging owing to the flow of the coolant. In this paper, temperature prediction using a thermal equivalent network is performed in an ISG that has a water cooled system. Then, an experiment is conducted to verify the thermal equivalent network.

Measurement of thermal properties by TPS-technique and thermal network analysis (TPS를 통한 열물성치 획득 및 네트워크모델을 이용한 열해석)

  • Yun, Tae-Sup;Kim, Young-Jin
    • Proceedings of the Korean Geotechical Society Conference
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    • 2010.09a
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    • pp.263-268
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    • 2010
  • Thermal characterization of geomaterials has significant implication on the geothermal energy, disposal of nuclear wastes, geological sequestration of carbon dioxides and recovery of hydrocarbon resources. Heat transfer in multiphase materials is dominated by the thermal conductivity of consisting components, porosity, degree of saturation and overburden pressure, which have been investigated by the empirical correlation at macro-scale. The thermal measurement by Transient Plane Source (TPS) and associated algorithm for interpretation of thermal behavior in geomaterials corroborate the robustness of sensing techniques. The method simultaneously provides thermal conductivity, diffusivity and volumetric heat capacity. The newly introduced thermal network model enables estimating thermal conductivity of geomaterials subjected to the effective stress, which has not been evaluated using previous thermal models. The proposed methods shows the applicability of reliability of TPS technique and thermal network model.

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Thermal Analysis of IPMSM with Water Cooling Jacket for Railway Vehicles

  • Park, Chan-Bae
    • Journal of Electrical Engineering and Technology
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    • v.9 no.3
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    • pp.882-887
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    • 2014
  • In this paper, the water cooling method among the forced coolant cooling methods is considered to be applied to the 110kW-class IPMSM for railway vehicles. First, basic thermal property analysis of the IPMSM is conducted using the three-dimensional thermal equivalent network method. Then, based on the results of the basic thermal property analysis, some design requirements for the water cooling jacket are deduced and a basic design of the water cooling jacket is carried out. Finally, thermal equivalent circuit of the water cooling jacket is attached to the IPMSM's 3D thermal equivalent network and then, the basic thermal and effectiveness analysis are conducted for the case of applying the water cooling jacket to the IPMSM. In the future, the thermal variation trends inside the IPMSM by the application of the water cooling jacket is expected to be quickly and easily predicted even at the design step of the railway traction motor.

Automatic adjustment of feedforward signal in boiler controllers of thermal power plants

  • Egashira, Katsuya;Nakamura, Masatoshi;Eki, Yurio;Nomura, Masahide
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.83-86
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    • 1995
  • This paper proposes an auto-tuning method of feedforward signal in boiler control of thermal power plants by using the neural network. The neural network produces an optimal feedforward signal by tuning the weights of the network. The weights are adapted effectively by using the teaching signal of PI control output. The proposed method was evaluated based on a detailed simulator which expressed non-linear characteristics of the 600 MW actual thermal power plant at load chaning operations, showed effectiveness in the learning of the weights of the neural network, and gave an accurate control performance in the temperature control of the system. Through the evaluation, the proposed method was proved to be effectively applicable to the actual thermal plants as the automatic adjustment tool.

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Prediction of temperature using equivalent thermal network in SPMSM (열 등가회로를 이용한 SPMSM 전동기의 온도 예측)

  • Kim, Do-Jin;Kwon, Soon-O;Jung, Jae-Woo;Hong, Jung-Pyo
    • Proceedings of the KIEE Conference
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    • 2008.07a
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    • pp.792-793
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    • 2008
  • This paper deals with the temperature calculation using equivalent thermal network for surface mounted permanent magnet synchronous motor(SPMSM) under the steady-state condition. In the equivalent thermal network, heat sources are generated from copper loss and iron loss. Heat transfer consists of conduction, convection and radiation. However, radiation is neglected in this paper because its effect is much smaller than others. Although the heat transfer coefficient in conduction use material property, heat transfer coefficient in convection is difficult to measure due to the atmosphere and ambient condition. Temperatures of each region in SPMSM are measured by thermocouple in operating condition and the thermal resistances of convection are calculated by kirchhoff's current law(KCL) and experimental result. In order to verify the validation and reliability of the proposed equivalent thermal network, temperature which is calculated other load condition is compared with experimental results. Accordingly, temperatures of each region in other SPMSMs will be easily predicted by the proposed equivalent thermal network.

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Evaluation of Thermal Embrittlement Susceptibility in Cast Austenitic Stainless Steel Using Artificial Neural Network (인공신경망을 이용한 주조 스테인리스강의 열취화 민감도 평가)

  • Kim, Cheol;Park, Heung-Bae;Jin, Tae-Eun;Jeong, Ill-Seok
    • Proceedings of the KSME Conference
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    • 2003.11a
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    • pp.1174-1179
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    • 2003
  • Cast austenitic stainless steel is used for several components, such as primary coolant piping, elbow, pump casing and valve bodies in light water reactors. These components are subject to thermal aging at the reactor operating temperature. Thermal aging results in spinodal decomposition of the delta-ferrite leading to increased strength and decreased toughness. This study shows that ferrite content can be predicted by use of the artificial neural network. The neural network has trained learning data of chemical components and ferrite contents using backpropagation learning process. The predicted results of the ferrite content using trained neural network are in good agreement with experimental ones.

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Evaluation of Thermal Embrittlement Susceptibility in Cast Austenitic Stainless Steel Using Artificial Neural Network (인공신경망을 이용한 주조 스테인리스강의 열취화 민감도 평가)

  • Kim, Cheol;Park, Heung-Bae;Jin, Tae-Eun;Jeong, Ill-Seok
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.28 no.4
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    • pp.460-466
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    • 2004
  • Cast austenitic stainless steel is used for several components, such as primary coolant piping, elbow, pump casing and valve bodies in light water reactors. These components are subject to thermal aging at the reactor operating temperature. Thermal aging results in spinodal decomposition of the delta-ferrite leading to increased strength and decreased toughness. This study shows that ferrite content can be predicted by use of the artificial neural network. The neural network has trained teaming data of chemical components and ferrite contents using backpropagation learning process. The predicted results of the ferrite content using trained neural network are in good agreement with experimental ones.

Dynamic Simulation of Annual Energy Consumption in an Office Building by Thermal Resistance-Capacitance Method

  • Lee, Chang-Sun;Choi, Young-Don
    • International Journal of Air-Conditioning and Refrigeration
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    • v.6
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    • pp.1-13
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    • 1998
  • The basic heat transfer process that occurs in a building can best be illustrated by an electrical circuit network. Present paper reports the dynamic simulation of annual energy consumption in an office building by the thermal resistance capacitance network method. Unsteady thermal behaviors and annual energy consumption in an office building were examined in detail by solving the simultaneous circuit equations of thermal network. The results are used to evaluate the accuracy of the modified BIN method for the energy consumption analysis of a large building. Present thermal resistance-capacitance method predicts annual energy consumption of an office building with the same accuracy as that of response factor method. However, the modified BIN method gives 15% lower annual heating load and 25% lower cooling load than those from the present method. Equipment annual energy consumptions for fan, boiler and chiller in the HVAC system are also calculated for various control systems as CAV, VAV, FCU+VAV and FCU+CAV. FCU+CAV system appears to consume minimum annual energy among them.

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Thermal Network Analysis of Interior Permanent Magnet Machine (매입형 영구자석 전동기의 열 등가 회로 해석)

  • Lim, Jae-Won;Seo, Jang-Ho;Lee, Sang-Yub;Jung, Hyun-Kyo
    • Proceedings of the KSR Conference
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    • 2009.05b
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    • pp.527-532
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    • 2009
  • Recently, Interior Permanent Magnet Machine(IPM) is widely used for traction motor in the high speed train. Due to the high efficiency and high power density of the IPM, it has lots of heat sources such as iron loss and copper loss. These heat sources can cause the demagnetization of permanent magnet, losses in output power and even irreversible defect of the IPM. To prevent the power loss caused by heat sources, the accurate thermal analysis has to be carried out. For the thermal analysis of the IPM, the thermal network is designed for this traction motor. The thermal analysis has executed at rated speed operation. The result of thermal network analysis can be used for the IPM design process.

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