Lumped Parameter Thermal Network Model Research Articles

Thermal Analysis of a Flux-Switching Permanent-Magnet Double-Rotor Machine With a 3-D Thermal Network Model

A fast and precise lumped-parameter thermal network (LPTN) model is presented for a flux-switching permanent-magnet double-rotor machine used for hybrid electric vehicles (HEVs), which has attracted attention due to the compact structure. The three-dimensional (3-D) LPTN model provides the steady-state thermal solution to derive the temperatures at different parts of the machine, in which the power losses of various working conditions are used as heat sources for calculating the temperatures of different operational modes. In the LPTN studies, a transformation of an irregular slot structure into a regular one is applied to simplify the calculation of the winding thermal resistance. A 3-D finite element thermal model of this machine is also established to calculate the temperatures of the main machine components for a comparative study purpose. Tests performed on the designed machine verify that the defined LPTN model has a high ability to predict the nodal temperatures accurately.

Thermal analysis and experimental verification of a staggered‐teeth transverse‐flux permanent‐magnet linear machine

To overcome the inherent demerit of low power factor existing in transverse-flux permanent-magnet (TFPM) machines, a tubular staggered-teeth TFPM linear machine is presented here. Linear alternator integrated with free-piston Stirling engines could offer a great potential in a wide variety of applications ranging from solar energy generation to space power supply. The thermal behaviour of the machine is studied using a three-terminal lumped-parameter thermal network (LPTN) to solve the problem of temperature overestimation of the traditional LPTN. The determination of thermal resistances and thermal parameters are introduced in detail. The temperatures of various components of the machine under different load conditions are calculated by both the three-terminal LPTN model and the numerical thermal model. Sensitivity analysis is carried out to study the influence of critical thermal parameters on the temperature rise of the machine. On this basis, the effectiveness of the forced air cooling is investigated. A prototype is fabricated and temperature experiment indicates that there is a good agreement between measurement and calculation.

Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module.

Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM) and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM) which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe). Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t|) °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR) technique and implemented into the real-time embedded system.

Lumped-parameter thermal network model and experimental research of interior pmsm for electric vehicle

A 25kW interior permanent magnet synchronous machine (IPMSM) applied to the electric vehicle is introduced in the paper. A lumped-parameter thermal network model is presented for IPMSM temperature rise calculation. Furthermore, a 3D liquid-solid coupling model considering the assembly clearance is compared with the 2D lumped-parameter thermal network model. Finally, a dynamometer platform for temperature rise measurement is established to verify the above-mentioned methods, which obtains the measured efficiency map at rated load case and overload case. At the same time, the measured no-load back electromotive Force (EMF), load line input voltage and load current are gathered. Thermocouple PTC100 is used to measure the temperature of the stator winding and iron core, and the FLUKE infrared thermal imager is applied to measure the surface temperature of PMSM and controller. Testing result shows that the lumped-parameter thermal network have a high accuracy to predict each part temperature.

Analysis of End-Winding Thermal Effects in a Totally Enclosed Fan-Cooled Induction Motor With a Die Cast Copper Rotor

Thermal overload protection techniques commonly use a simplified 1st order thermal model, which does not provide accurate stator winding temperature prediction and causes frequent undesirable stoppage of the motor in the processes. This paper proposes a higher order lumped parameter thermal network model to accurately predict stator winding temperature. First, the comparison of the predicted stator winding temperature from a 1st order thermal model with a higher order thermal model is performed. Second, a comparison between the actual and the predicted stator winding temperature rise is verified for a 20 hp totally enclosed fan-cooled copper rotor induction motor that has no rotor fins on its short-circuit ring to enhance heat dissipation compared with an aluminum rotor induction motor.

Inverse modeling of the urban energy system using hourly electricity demand and weather measurements, Part 2: Gray-box model

The interpretation of the energetic signature of a city, taken as an integrated urban energy system, has been attempted in this study. Instead of the customary bottom-up approach, we successfully identified an average gray-box dynamic model by inversion of measured hourly system load and weather data. The third-order lumped-parameter thermal network model is derived by applying energy conservation principles to major nodes representing buildings, paved surfaces and urban canopy. This powerful data-driven approach offers deep insights into the thermo-physical properties of the built structures as well as the coupling of buildings and the urban microclimate. In particular, the Urban Heat Island (UHI) intensity has been determined to be close to 2°C while the corresponding electricity cooling load penalty is 12%.

A new model of urban cooling demand and heat island—application to vertical greenery systems (VGS)

The relationship between Urban Heat Island (UHI) and energy consumption in buildings has been widely observed and studied. The aim of this paper is to investigate the impact of large-scale deployment of indirect Vertical Greenery Systems (VGS) on the cooling demand of buildings and on the urban microclimate. VGS significantly reduces air temperature and wind speed near the walls. In doing so, it also positively impacts the UHI intensity. This is achieved mainly through the conversion of sensible heat to latent heat mediated by evaporation and transpiration from the VGS foliage. Evapotranspiration is a physically complex phenomenon and its interaction with the building and the urban climate is difficult to model accurately. We propose to use a dynamic nonlinear lumped parameter thermal network model to determine the thermal interactions between the prototypical building, the VGS, the paved road, the urban canopy air and the atmosphere. The model accounts for both sensible and latent exchanges within and outside the building. Solar (short-wave) radiation on building façade and road accounts for shading and unlimited diffuse reflections. Long-wave radiation among surfaces and between surfaces and the sky are estimated using view factors and the fully nonlinear Stefan-Bolzmann law. Building envelope infiltration rate and convective heat transfer coefficient vary with wind speed so as to properly reflect the energetic impact of wind speed attenuation near the wall due to the foliage. The thermal and aerodynamic characterization of the vegetation is based on the formulations proposed by Deardorff (1978). The evapotranspiration rate is estimated based on the Penman formula and is driven by the ‘vapor pressure deficit’ between actual vapor pressure in the ambient air and the saturation vapor pressure assumed to prevail on the surface of leaves. The calculation of sensible and latent heat fluxes between the urban canopy and the first level of the atmosphere considers buoyancy effects, using the coefficients introduced by Mascart et al. (1995). First, a base case model (no VGS) is created and validated using both building energy consumption data and urban air temperature measurements. The validated model is then used to investigate the impact of a large-scale deployment of VGS in the urban context. The weather data and the typical building thermo-physical properties are from the UAE. Comparison of the urban base case to the rural base case (both without VGS) shows a cooling load penalty, due to the UHI, of about 7%. Retrofitting VGS to all buildings in the urban domain of study results in a 5−8% reduction of the cooling load and a dramatic drop of the urban air temperature of about 0.7−0.9°C, reducing the UHI intensity by almost half.

Thermal Real-Time Monitoring of a Gearbox Integrated IPM Machine for Hybrid-Electric Traction

Aiming to monitor the temperatures of critical components of gearbox integrated interior permanent magnet synchronous machines for hybrid-electric vehicles, we present the development of a real-time lumped parameter thermal network model. To this aim, sensitivity and heat flow path analyses are first carried out to identify the most relevant thermal paths. Next, the influence of the gearbox integration on the temperatures within the electric machine and its consideration in the modeling are investigated. The models are then verified experimentally, showing an accuracy of ±5 K. Finally, challenges and uncertainties of the real-time on-board modeling context are ultimately discussed.

Multiobjective Optimal Design of Switched Reluctance Linear Launcher

In this paper, based on the comparisons of the stator pole flux density and phase current with corresponding rotary switched reluctance machine, the original design scheme of a 1-kW single-side switched reluctance linear launcher (SRLL) is obtained by a traditional method. To get higher efficiency and smaller force ripple, the genetic algorithm, which is improved to enhance the convergence rate and global accuracy, is applied to optimize the original design scheme. The global optimum values of key dimensions and control parameters are obtained, and the detailed structure of whole SRLL is given as well. Then a detailed equivalent lumped-parameter thermal network (LPTN) model of the considered SRLL is built, and temperature rises of some parts are obtained. To test the feasibility of the LPTN model, a 2-D finite element thermal model of the SRLL is built, and the temperature rises are obtained. The results from LPTN model match those from the finite-element method very well. Finally, the preliminary tests of the prototype of designed SRLL are carried out and the experimental results are presented.