Numerical Analysis and Optimization of Thermal Performance of LED Filament Light Bulb

Transcription

1 2017 IEEE 67th Electronic Components and echnology Conference Numerical Analysis and Optimization of hermal Performance of LED Filament Light Bulb Jie Liu 1, Chunlin Xu 2, Huai Zheng 1, *, and Sheng Liu 1 1 School of Power and Mechanical Engineering, Wuhan niversity Wuhan, , China 2 School of Mechanical Science & Engineering, Huazhong niversity of Science & echnology Wuhan, , China huai_zheng@whu.edu.cn Abstract his paper presents numerical studies on thermal performance of LED light bulbs with different bulb sizes, phosphor diameters, and phosphor shapes. A quarter of numerical model of LED light bulbs was built to analyze the temperature field, velocity field and distributions for convective heat flux coefficient on the surface. he effects of bulb sizes, phosphor diameters and phosphor shapes on the thermal performance were investigated. he imum temperature of a type of commercial LED light bulb reaches 145, which can be reduced by the increasing of bulb sizes and phosphor diameters. When the phosphor diameter increases from 2 mm to 5 mm, the imum temperature is reduced by 24, which is also decreased by 10 with the increased bulb size of 4 mm. In addition, -shape s can effectively reduce the bulb temperature, and the imum temperature reduction is 10 when the length reaches 0.91 mm. Keywords-LED; bulb; thermal; simulation; optimization I. INRODCION Light-emitting diode (LED) is known as the next generation illumination technology [1]. he LED light bulb has received great attention and is replacing conventional lights owing to its high efficiency, energysaving, environmental protection, and long lifetime [2-3]. However, the LED bulb with a special packaging structure has a poor heat dissipation, which is mainly caused by the space limit and convection cooling method [4]. his issue lead to the overheating and poor luminous efficiency [5-6]. In order to solve this problem, thermal design and management is an effective method for the LED light bulb. Studies on the optimal design of the LED bulb have been extensively carried out based on both experimental and numerical methods. he LED cooling system is optimized in such aspects as structure, materials and manufacturing processes. For instance, the use of large chip flip-chip package structure [7]; selecting the appropriate substrate material and adhesive material [8], with silicone resin instead of epoxy resin; filled with high thermal conductivity gases such as helium [4] and Al 2O 3 nanofluid [9]. In this study, the thermal performance of LED light bulb was studied and optimized. A quarter of numerical model of LED light bulb was built to investigate the effects of bulb sizes, phosphor diameters, and phosphor shapes on the thermal performance. According to the analysis results, optimal designs on bulb sizes, phosphor diameters, and phosphor shapes for the LED light bulb were studied and ally optimal thermal performances were achieved. II. SIMLAION MODEL In order to reduce the amount of numerical simulation calculation, a quarter of 3-D computational model was established, as shown in Fig. 1. here are 4 s in one complete LED bulb and 28 LED chips on each. he cross-section of the cylindrical is show in Fig. 2. he computational analysis domains include the glass wall, cylindrical, and surrounding air. he major parameters are shown in ABLE. 1. Fig. 1. Numerical model establishment /17 $ IEEE DOI /ECC

2 Fig. 2. Cross section of cylindrical. ABLE 1. Major Properties Setting. Item Properties Value LED chips hermal power (W) 0.02 Copper substrate hermal conductivity(w/(m K)) 400 Phosphor hermal conductivity(w/(m K)) 0.3 Glass wall hermal conductivity(w/(m K)) 1.09 Glass wall surface Heat transfer coefficient(w/(m² K)) 5 air hermal expansion coefficient(1/k) 2.72E-03 A tetrahedral mesh was used and the mesh distance decreased near the, as shown in Fig. 3. he computation model is composed of 791,117 girds for the simulation of thermal behaviors. A grid independence test was performed by changing the number of grids from 791,117 to 1,132,984 and the variation of imum bulb temperature of the heat sink is less than 0.4%. o simulate natural convection, the following assumptions were made: (1) he ow is steady and three dimensional. (2) he surrounding air is set as an ideal gas and its properties are constant [10]. (3) Radiative heat transfer is negligible because of the small single chip power. he govern equations of the non-isothermal air flow are: Continuity equation: ( ρu ) = 0 1 Momentum conservation equation: ρ ( ) = μ + μ + 2 u u pi u u 3 u I + F 2 where F is the volume force, along the vertical direction of gravity, is given by the equation: F = ρgαδ 3 where α is the gas thermal expansion coefficient. he convective and conductive heat transfer inside the bulb is described by the energy conservation equation: ρc u + ( kδ ) = Q 4 P where Q refers to the power density in the that serves as a heat source. he power of a single chip is 0.02W, heating power accounted for 65%. he Nusselt number is an important non-dimensional parameter in heat transfer study that describes the intensity of convective heat transfer and dened as follows: hl Nu = 5 λ where h is the surface heat transfer coefficient between fluid-wall. l is the size dimension and as the case may be. λ is the thermal conductivity. III. RESLS AND DISCSSION Fig. 4 illustrates the simulation results of the temperature distribution of LED bulb. Fig. 4(b) and Fig. 4(c) shows the temperature distribution of longitudinal and cross section respectively. nder this setting the highest temperature of the LED bulb is about 145, near the. And average temperature of chips is about 143. In contrast, the lower part of the bulb temperature is low. Fig. 3. Numerical mesh (a) Whole LED bulb 2244

3 convection. It can be seen that the natural convection process has a great impact on LED bulb temperature. So the next work can be carried out by increasing convective heat transfer intensity of the surface and glass wall. (b) Longitudinal section (a) Whole LED bulb (b) Filament longitudinal section Fig. 5. Velocity distribution of the LED bulb. (c) Cross section Fig. 4. emperature distribution of LED bulb. As shown in Fig. 4(c), the LED bulb cross section is divided into 7 parts.. By comparison, the part 1 and part 5 are the gas inside the LED bulb, whose temperature changes gently. he part 3 and part 7 denote the cylindrical and glass wall. he temperature of the rest parts change relatively larger. hey are the part 2 and part 4 near the, part 6 near glass wall. hese parts with large temperature fluctuation are mainly dissipating heat by Fig. 5 illustrates the simulation results of the velocity distribution. As can be seen, the velocity field appears vortex-like and the imum velocity is about m/s, near the. he temperature difference is the main cause of the air flow. So the velocity is relatively high near the and glass wall. Bulb volume also limits the development of the velocity field in a certain extent. Fig. 6 illustrates the heat transfer coefficient distribution on the surface. he distributions on top and bottom surface of the are shown in Fig. 6(a) and Fig. 6(b) respectively. 2245

4 (a) op Surface Fig. 7. the outline of original, increase 2 mm and increase 4 mm (b) Bottom Surface Fig. 6. Heat transfer coefficient on the he size of the heat transfer coefcient expresses the intensity of the convective heat transfer. It shows higher values near the tip, which mainly distributed in the top surface and bottom surface. More precisely, there are the junction of the top and side, bottom and side, phosphor and copper substrate. And the lower values appear the side of the. As a whole, heat transfer coefficient on the top surface was greater than the lower surface. he average value of heat transfer coefficient on the surface is obtained by averaging the value of heat transfer coefficient over the entire surface. he average value of heat transfer coefficient is W/(m² K). his belongs to the natural convection, which surface heat transfer coefficient in natural convection of air is about 5~25 W/(m² K). Based on the above discussion, three optimization schemes were proposed. hey are optimized for the bulb sizes, phosphor diameters and phosphor shapes. he thermal performances were further analyzed by changing these conditions. A. Effect of Bulb sizes On the basis of the above model, the glass wall size is increased by 2 mm and 4 mm, respectively, as illustrated in Fig. 7. he thermal simulation results compared with the original are shown in ABLE. 2. Item ABLE 2. Simulation Results of Different Bulb Sizes. d (mm) chi p V (m/s) h (W/(m² K)) Original Increase 2mm Increase 4mm Where d is the phosphor diameter, V and is the imum velocity and temperature in the whole bulb respectively, chi p is the average temperature of 28 chips and h is the average heat transfer coefficient of surface. As illustrated in ABLE. 2, the increasing of bulb wall can obviously reduce and. When the bulb size chi p increases 2 mm, the temperature is reduced by 5. he increasing of V is mainly due to the weakening effect of the bulb volume limitation. he velocity field is favorable for convective heat transfer and will promote heat dissipation. h and N increase at the same time, which indicates the enhancement of convective heat transfer on the surface. B. Effect of Phosphor Diameter he phosphor diameter was designed as 2 mm, 3 mm, 4 mm, and 5 mm, respectively. he thermal simulation results compared with the original are shown in ABLE. 3. N 2246

5 d (mm) ABLE 3. Simulation Results of Different Phosphor Diameters. chi p V (m/s) h (W/(m² K)) Filament surface area(mm²) As illustrated in ABLE. 3, and chi p decrease with the increasing of phosphor diameter, and the imum temperature reduction is 24 with the phosphor diameter increasing from 2 mm to 5 mm. While V and h is gradually reduced. he surface area increases with the phosphor diameter. As the phosphor diameter increases, the space inside the bulb reduces and the limiting effect of the velocity increases. Simultaneously, the convective heat transfer area increases, which can reduce the thermal resistance of convection heat transfer, resulting in the enhancement of convective heat transfer process of the. Even though both the speed and average convective heat transfer coefficient are reduced, the LED bulb temperature is still reduced. N is consistent with the increasing of phosphor diameter, which indicates the enhancement of convective heat transfer on the surface. It is possible to optimize the phosphor diameters by appropriately increasing the diameter. C. Effect of Phosphor Shapes Some of the heat exchanger surfaces are ned to enhance heat transfer. Such as condensers, radiators, air heaters of refrigeration devices and so on. Reference the characteristics of s increasing the heat dissipation surface area and enhancing heat transfer, setting lace s with radial s on the phosphor. Here set up two types of lace s, which the main difference is the length. he cross-sections of different phosphor shapes are shown in Fig. 8. he thermal simulation results compared with the original are shown in ABLE. 4. N I = 0.61mm I = 0.91mm l (mm) ABLE 4. Simulation Results of Different Phosphor Shapes. () chi p () V (m/s) h (W/(m² K)) Filament surface area(mm²) Δ N Where l is the length of s. Considering the shape characteristics of the, Δ N is the difference of Nusselt number compared to the original model ( l = 0mm). As illustrated in ABLE. 4, and chi p decrease with the increasing of l. l increases from 0.61 to 0.91, the imum temperature reduction is 7 and 10, respectively. V and h decrease at the same time. Δ N varies from 0 to and , indicating the enhancement of convective heat transfer on the surface. he ned structure can significantly increase the surface area than cylindrical with the same diameter. his is more effective to reduce the convective heat transfer resistance. Fin-shape s can effectively reduce the temperature. IV. CONCLSIONS In this study, a simulation model of LED light bulb was built. sing N or Δ N to evaluate the intensity of convective heat transfer. he simulations of temperature field, velocity field and convective heat flux coefficient on the surface were shown and the thermal performance optimizations were further analyzed by changing the bulb size, phosphor diameter, and phosphor shapes. It is found that the increasing of the bulb sizes can obviously reduce bulb temperature, and the imum reduction is 10. he increasing of the phosphor diameters enhances the overall convective heat transfer and the al temperature decreases; the imum reduction is 24. Finshape s can effectively reduce the temperature; and the longer the, the lower the temperature; the imum reduction is 10. And based on the discussions mentioned above, the optimization for a LED light bulb can be implemented by appropriately increasing bulb sizes, increasing diameters or using Fin-shape s. Fig. 8. Cross-sections of different phosphor shapes. ACKNOWLEDGMEN his work is supported by National Natural Science Foundation of China (Grant Nos and ), and the Natural Science Foundation of Hubei Province (Grant No. 2015CFA060). 2247

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