A New Noncontact Method for the Prediction of Both Internal Thermal Resistance and Junction Temperature of White Light-Emitting Diodes

Xue, Tao; Chen, Huan-Ting; Li, Sinan; Hui, S.Y.R.

doi:10.1109/tpel.2011.2169461

Cited by 25 publications

(11 citation statements)

References 19 publications

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“…The luminous flux is a part of radial flux, which stimulates human eye light perception and can be denoted by V ( λ ), also expressed as Φ, with its unit as W . In addition, the unit of luminous flux can also be denoted as “lm” in visible light, which is shown as ,

normalΦ = \int P (λ) V (λ) dλ

where λ is wavelength, P ( λ ) is a function of radial flux changing with the wavelength, which is also called spectral power distribution. In a very narrow band range, the radial flux corresponding to d λ is given in , and the total radial flux is expressed in , respectively, or

normald normalP = normalP (λ) normald λ

P = \int P (λ) dλ

…”

Section: Basis Of Photometrymentioning

confidence: 99%

“…Luminous intensity is the lighting state of a radiator at a given direction in space. It is defined as luminous flux in unit solid angle at a certain direction, given by

I = \frac{d normalΦ}{d normalΩ}

where Φ is luminous flux, and Ω denotes a solid angle.…”

Section: Basis Of Photometrymentioning

confidence: 99%

“…Let dΦ φ be the luminous flux emitted in dΩ, and dΩ be the solid angle that is in the angle φ between the micro area and the surface normal vector N . The luminous intensity for φ is given in , and the luminance of d S in the direction of φ is the ratio between I ( φ ) at the direction of φ and d S c o s φ , expressed by , or

I (φ) = \frac{normald {normalΦ}_{φ}}{normald normalΩ}

L ((), φ) = \frac{I ((), φ)}{normald S \cos φ}

…”

Section: Basis Of Photometrymentioning

confidence: 99%

See 2 more Smart Citations

Channel modeling for visible light communications—a survey

Qiu

Chen

Meng

2016

Wireless Communications

120

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Visible light communication (VLC) is a newly emerging technology, which integrates communications and lighting purposes, and has become a very active research topic in the areas of wireless communications. It is expected to become an important part of the next generation wireless communications because of its unique features in using unlicensed spectrum, support of high data rate, and its resistance to electromagnetic interferences. In this survey paper, we begin with a review on the basis of photometry, which is used to establish channel models of VLC systems. Then, we will continue to address various issues on the fundamental characteristic features of VLC systems, the impact of indoor environments on system performance, and the analysis and discussions of five different types of typical VLC channel models and other related parameters in VLC channel models. Finally, in terms of the future works, we will show the possible follow-up research focuses and directions as an effort to identify some new research topics on VLCs. Visible light communicationsFigure 1. Diagram of current spectrum resource usage.authorities and spectrum usage fees. On the other hand, the electromagnetic spectrum bands in RF is fairly limited and controlled strictly by the regulatory authorities, resulting in a high cost of usage and maintenance of the RF spectral resources. Meanwhile, VLC supports high data rate optical communications and facilitates the bandwidth reuse. Therefore, VLC can be employed to support very high data rate wireless communications [10][11][12][13][14][15][16][17].Second, VLC is much securer than RF communications. Transmission medium of VLC is visible light, which cannot penetrate walls and other non-transparent objects in an indoor environment, and thus, its transmission is limited in the line of sight (LOS). This means that the transmission of user data information is confined to a room, and it is much more difficult for eavesdroppers to intercept communication content without being noticed by the senders in the same room. In this way, transmission of data information can be carried out effectively without external malicious interceptions, and security of information can be ensured. Therefore, VLC offers a highly confidential means of wireless communications particularly suitable for military and other secure information communication applications [12][13][14][15][16][17][18][19]. In millimeter wave communications, the wireless signal attenuation is rapidly near 60 GHz, but its security is by far not as good as VLC systems [20].Third, VLC is not hazard to human health. We can use a higher transmission power in VLC if it is needed than normal RF communications. Compared with infrared and ultraviolet communication technologies, VLC can be implemented in a more comfortable way because of human eyes visual perception nature, and thus, it allows us to use a greater transmission power in order to improve communication link quality [12][13][14][15].In addition, VLC in visible lightwave bands, which are quite different fr...

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normalΦ = \int P (λ) V (λ) dλ

normald normalP = normalP (λ) normald λ

P = \int P (λ) dλ

…”

Section: Basis Of Photometrymentioning

confidence: 99%

“…Luminous intensity is the lighting state of a radiator at a given direction in space. It is defined as luminous flux in unit solid angle at a certain direction, given by

I = \frac{d normalΦ}{d normalΩ}

where Φ is luminous flux, and Ω denotes a solid angle.…”

Section: Basis Of Photometrymentioning

confidence: 99%

I (φ) = \frac{normald {normalΦ}_{φ}}{normald normalΩ}

L ((), φ) = \frac{I ((), φ)}{normald S \cos φ}

…”

Section: Basis Of Photometrymentioning

confidence: 99%

See 1 more Smart Citation

Channel modeling for visible light communications—a survey

Qiu

Chen

Meng

2016

Wireless Communications

120

View full text Add to dashboard Cite

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“…k h is not constant for a single LED, varying with T J and P el [28]. As P el is a function of I F and T J , P heat can be calculated as…”

Section: A Led Electro-thermal Modelmentioning

confidence: 99%

A Lifetime Prediction Method for LEDs Considering Real Mission Profiles

Wang

Zhan

et al. 2017

IEEE Trans. Power Electron.

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The Light-Emitting Diode (LED) has become a very promising alternative lighting source with the advantages of longer lifetime and higher efficiency than traditional ones. The lifetime prediction of LEDs is important to guide the LED system designers to fulfill the design specifications and to benchmark the cost-competitiveness of different lighting technologies. However, the existing lifetime data released by LED manufacturers or standard organizations are usually applicable only for some specific temperature and current levels. Significant lifetime discrepancies may be seen in the field operations due to the varying operational and environmental conditions during the entire service time (i.e., mission profiles). To overcome the challenge, this paper proposes an advanced lifetime prediction method, which takes into account the field operation mission profiles and also the statistical properties of the life data available from accelerated degradation testing. The electrical and thermal characteristics of LEDs are measured by a T3Ster system, used for the electrothermal modeling. It also identifies key variables (e.g., heat sink parameters) that can be designed to achieve a specified lifetime and reliability level. Two case studies of an indoor residential lighting and an outdoor street lighting application are presented to demonstrate the prediction procedures and the impact of different mission profiles on the lifetime of LEDs.

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“…The third temperature evaluation method is based on TSEPs such as saturation current, gate-emitter voltage, threshold voltage and collector-emitter voltage correlated with temperature [16][17][18][19][20][21][22]. The largest advantage of TSEP measurement is that it can be performed on packaged power modules [16].…”

Section: Introductionmentioning

confidence: 99%

Junction Temperature Prediction of IGBT Power Module Based on BP Neural Network

Wu¹,

Zhou²,

Du³

et al. 2014

Journal of Electrical Engineering and Technology

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-In this paper, the artificial neural network is used to predict the junction temperature of the IGBT power module, by measuring the temperature sensitive electrical parameters (TSEP) of the module. An experiment circuit is built to measure saturation voltage drop and collector current under different temperature. In order to solve the nonlinear problem of TSEP approach as a junction temperature evaluation method, a Back Propagation (BP) neural network prediction model is established by using the Matlab. With the advantages of non-contact, high sensitivity, and without package open, the proposed method is also potentially promising for on-line junction temperature measurement. The Matlab simulation results show that BP neural network gives a more accuracy results, compared with the method of polynomial fitting.

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A New Noncontact Method for the Prediction of Both Internal Thermal Resistance and Junction Temperature of White Light-Emitting Diodes

Cited by 25 publications

References 19 publications

Channel modeling for visible light communications—a survey

Channel modeling for visible light communications—a survey

A Lifetime Prediction Method for LEDs Considering Real Mission Profiles

Junction Temperature Prediction of IGBT Power Module Based on BP Neural Network

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