3 Multispectral Mixing Optimization as Lens Design Techniques
3.6 Tolerance analysis
Finally, the designer can sequentially introduce a small perturbation to each parameter (ˆ, Δλ, IDC, Ta) and observe the corresponding change. It is noted that the presented technique merely confine the discussion to the spectral range, it is not likely to predict the light field changed by the geometric deviation such as LED package error or assembly misalignment. A possible compensation mechanism which constantly measures the SPD on the illuminated plane and gives feedbacks to drive currents might be helpful to tolerance the LED cluster .
3.7 Summary and conclusions
A novel LED mixing scheme analogous to the conventional lens design process has been proposed. The algorithm enables the users to easily determine the optimal LEDs set to meet the requirements such as light efficiency, color quality, or other figures of merit over a wide range of color temperature. The procedure includes six steps: (3.1) initial system, (3.2) define boundary condition, (3.3) optimization, (3.4) merit analysis, (3.5) judgment, and (3.6) tolerance analysis, and each step has been carefully considered in turn.
We list three suggestions for initial system to pick appropriate LED set from the
“LED map”. After that, domains of input variables (i.e. the drive current IDC and ambient temperature Ta) and the additional confinement (e.g. xy < 0.01) should be predefined before going through optimization process. To obtain the optimal composite spectrum, a globe searching engine, continuous genetic algorithm CGA has been adopt with eight iterative processes in Figure 3-3. Based on the user-defined merit function, we correspondingly proposed two sampling methods SA1 and SA2, to improve the computational efficiency and costly analyze the cluster performance among figures of merit. For the system is under qualified, three skills presented in Section 3.5 may allow the operation in adequate margin. Finally, with a small perturbation to each parameter, the tolerance of the optimized system can be observed.
Chapter 4
Applications of the Multispectral Mixing Scheme
4.0 Goal
The proposed mixing scheme in previous chapter theoretically provides more efficient optimization for multispectral LEDs clusters than is provided by previous researchers.
In this chapter, we realize the mixing scheme into two examples individually adopting (1) low power LEDs cluster and (2) high power LEDs cluster. Both of them are planned for general lighting use. Therefore, they share the same merit function MF that is identical to Equation (3-15), where the merits of figure composed of color quality scale CQS and luminous efficiency LE are linearly combined by weighted sum method. For the low power LEDs case, the objective is to demonstrate how a LEDs cluster with high luminous efficiency (LE is 97% of cluster’s theoretical maximum value) and high color quality scale (CQS > 80 points) can be generated by following the devised methodology step-by-step. After that, we aim to release the constraint of the constant ambient temperature on LEDs system and extend the thermal operation window for the high power LEDs case. The result shows that the proposed method is experimentally validated to offer a full operable range in ambient temperature (Ta
from 10° to 100°C) associated with high CQS (above 85 points) as well as high LE (above 100 lm/watt).
4.1 Case 1: Low power LEDs cluster design
We setup a multispectral platform composed of four single-colour LEDs (Excellence Opto. Inc., EOQ-5ERF red, EOQ-5EYF amber, EOQ-5DFE green, EOQ-5EBF blue) and a phosphor-converted cool-white LED (Excellence Opto. Inc., EOQ-5EWF). The corresponded spectra at ambient temperature Ta of 25 oC and drive currents IPWM of 20 mA are shown in Figure 4-1. An adequate layout of LED arrangement and optics with first-order design are considered to deliver a uniform illumination on the measured plane . Due to the relative low level of drive currents (maximum 20mA) controlled by the pulse-width modulation (PWM) approach, the modeling of the spectral power distribution SPD for each colour LED can be assumed to satisfy the scalability and additive property in color mixing scheme , which indicates the SPD can be thermal -independent and be regularly proportional to drive currents without distortion.
Figure 4-1 The spectra of red (R), green (G), blue (B), amber (A) and cool-white (CW) LEDs at ambient temperature Ta of 25 oC with all drive currents of 20 mA. The corresponded chromaticity points and specifications are also shown in the figure. The drive currents controlled by PWM approach have the pulse width of 6.66 ms at differences of 0.04 ~ 0.06 ms for each gray level (a total of 128 gray levels).
4.1.1 Validation of the composite spectrum
As the aforementioned process, we start to fulfill the models of multispectral LEDs through optimization step with weight factors w = 0 (efficiency mode) and 1 (quality mode). The resultant spectra for color temperatures CT = 3000K and 6500K are selected to be verified as shown in Figure 4-2, where the simulations are in close agreement with the experimental measurements by checking the R2 value (above 0.98) and the chromaticity deviation xy (below 0.01). The Figure 4-3 features illuminant environments for both color temperatures 3000K and 6500K at the efficiency mode.
Apparently the appearance of the color checker chart is more accurate in the booth with higher CQS than that in the booth with poor CQS (refer to the difference of the grey scale coloured squares between these booths).
Figure 4-2 Spectral comparisons of simulations and experiments for P0 and P1 at CTs of 6500K and 3000K, respectively. The simulated spectra closely
Figure 4-3 The illuminant environments at (a) P0 (CQS = 87 points, LE = 66 lm/watt) for CT= 6500K and (b) P0 (CQS = 69 points, LE = 67 lm/watt) for CT = 3000K show apparently different color rendering abilities.
4.1.2 Comparison of R/G/B and R/G/B/A system
In addition to the experimental validation, more insight can be pursued by the quantitative analyses. Here we assume the minimum requirements for color rendering CQSm = 80 points and luminous efficiency LEm = 60 lm/watt. Based on the linear approximation SA2 method, the loci of R/G/B, R/G/B/A, and R/G/B/A/CW are presented in Figure 4-4. The black curve in Figure 4-4(a) depicts the referenced single solution of R/G/B cluster for color temperature CT from 1000K to 10000K. It can be noted that all of the solutions are far from the required performance (quadrant I). We than add the amber (A) source to the R/G/B cluster, the average improvement of 50%
in color quality scale CQS is achieved without too much loss of luminous efficiency (LE1/0 < 5%). This result is generally in accordance with the concept that the color rendering performance of sources would be improved when its modulated spectrum is as smooth as sunlight.
For the solution of each color temperature CT, the point P0 (w = 0) is set as the starting point as we mentioned in the Section of merit analysis. In the view point of P0, the information of the increment rate of CQS denoted as CQS1/0 and the sacrifice of
decrement rate of LE denoted as LE1/0 can be given in Figure 4-5. The result of the R/G/B/A case shows that all circle points for whole range of color temperature CT are located at right-top corner. Thus the designer would undoubtedly chose a high weight value (w ~ 1) to boost the color rendering ability with a little expense of cluster efficiency. This tendency is equivalent to drive P0 to approach P1 along the straight line in Figure 4-4 (a). Nevertheless, the R/G/B/A cluster still suffers a stringent operating window of CT from 2800K to 3000K, which would strictly preclude its use in intelligent lighting applications.
Figure 4-4 The SA2 results of (a) R/G/B (black curve), R/G/B/A, and (b) R/G/B/A/CW clusters aimed to P1 and P0 for full range of CT from 1000K to 10000K.
Figure 4-5 The results of CQS1/0 and LE1/0 for R/G/B/A and R/G/B/A/CW clusters. By using SA2 analysis, R/G/B/A/CW can further extend the operation window in color temperature.
4.1.3 The effect of cool-white LED
Compared with the R/G/B/A cluster, the addition of cold-white (CW) LED is able to further extend the operational window throughout the entire color temperature range.
To prove this statement we can select a start point P0 at CT= 3000K, whose CQS0 = 66.8 points (unqualified) and LE0 = 66.7 lm/watt [refer to Figure 4-4 (b)]. The corresponded information of CQS1/0 = 34.3% and LE1/0 = −2.4% at the same point P0
can be found in Figure 4-5. With above parameters, it is readily to derive an appropriate weight of 0.79 by using Equation (3-17) to fulfill the requirement, where the CQS value is increased to 85 points at the expense of 1.3 lm/watt.
Generally, the weighting value can be conducted to the comparison between CQS1/0 and LE1/0. That means the balance condition of CQS1/0 ≈ −LE1/0 at color temperature CT of 5200K (Figure 4-5) could be regard as a turning point for the weight selection. By applying this weight value selection strategy to the R/G/B/A/CW combination, it is logically to choose a large weight value (w > 0.5) for CT < 5200K
and vice versa in order to approach the requirements. In sum, adapting the phosphor- converted white source could further increase 5% in CQS and 20% in LE over full range of color temperature, which is due to the cool-white LED associated with high efficiency offers a good candidate to substitute the function of blue colour. The detail will be analyzed as follows the illustration of Figure 4-6.
Figure 4-6 (a) The values of CQS and LE, and (b) the stacked emission power ratio versus color temperature for the optimized R/G/B/A/CW design (CQSm = 80 points and LEm = 60 lm/watt). The operation window has been extended to 2600K < CT < 8500K with the selected weight via SA2 selection method. It is noted that the operation window is mainly restricted by the CQS due to the correction factor at the extreme color temperature.
4.1.4 The color tunable R/G/B/A/CW system
At this point, we can successfully determine the operation point by the proposed methodology and set an optimal lighting environment for R/G/B/A/CW system. As shown in Figure 4-6, the operation window is extended to span across 2600k − 8500K with the user-defined requirements of CQSm = 80 points and LEm = 60 lm/watt, which would be shrink by more severe lighting requirement accordingly (e.g. the operation window of 3200 − 5600K for CQSm = 90 points and LEm = 64lm/watt).
Based on Figure 4-6, we can find that when the color temperature is less than the 6400K, the power ratio is mainly governed by the light quality requirement, and each component has a comparable amount. On the other hand, the efficiency requirement is dominated and contributed by cool-white LED when the operation temperature is higher than 6400K. The combination of LED cluster reduces to R/G/CW for 6400K <
CT < 8500K as shown in Figure 4-6 (b). Within the operation window of 2600K ― 8500K, the function of blue LED has been replaced by the cool-white light source, so that we can discard it from the cluster for most general lighting applications.
4.2 Case 2: High power LEDs cluster design
In the high power multispectral mixing, the thermal issue is no longer independent but should be included in spectrum prediction as we modeled in Chapter 2. In contrast to low power design, in this section we setup another pentachromatic mixing platform, where a high-power LEDs cluster is composed of four single-colour LEDs (HELIO Optoelectronics Corp., HMHP-E1HR red, HMHP-E1HA amber, HMHP-E1HG green, HMHP-E1HB blue) and a phosphor-converted HMHP-E1HW white LED. Figure 4-7 shows the spectral power distribution SPD of each channel under operational condition Ta = 10 oC and IDC = 350 mA, respectively. An adequate
layout of LED pixel arrangement and first-order design delivers a uniform illumination upon the test Macbeth color checker .
Figure 4-7. The power spectra of red (λR: 625nm, ΔλR: 20nm), green (λG: 523nm, ΔλG: 33nm), blue (λB: 465nm, ΔλB: 25nm), amber (λA: 587nm, ΔλA: 18nm) and cool-white LEDs at Ta of 10 oC with IDC of 350 mA. The upper right figure shows a real-field test designed for CT = 5000K and the lower right one shows the utilized LEDs attached on the temperature controllable fixture respectively.
4.2.1 The influence of ambient temperature on color mixing
The first validation of the devised model is conducted by examining the temperature dependence of spectra under four color temperatures: CT = 3200K, 4600K, 6200K, and 7400K, respectively. The system is operated under a specific value of the ambient temperature, Ta = 50 oC. The results are reported in Figure 4-8, where the illumination conditions fulfill the requirements of high luminance level (100 lm), negligible color deviation (Δxy < 0.01) and high quality (CQS > 85 points) with possibly highest luminous efficiency LE. If we change the ambient temperature without compensation,
CT = 3200K for example, as ambient temperature increases from 10 oC to 100 oC, the chromaticity point would have an apparent change (Δxy > 0.5). On the other hand, in case of settled operational ambient temperature Ta = 50oC, the acceptable tolerance (Δxy < 0.01) of thermal dependence merely lie in a tiny window Ta = 42 oC ~ 56 oC. It is observed that the operational window changes with respect to different chromaticity points. The drift of chromaticity point subject to thermal dissipation becomes more severe at low CT, which is mainly attributed by amber and red color. The reason can be explained by Figure 4-9.
Figure 4-8. The temperature dependence of spectra designed for CT = 3200K, 4600K, 6200K, and 7400K at Ta = 50 oC. The chromaticity point shifts toward higher color temperature with the raise of Ta owing to the dramatic deterioration in LEs of the red and amber LEDs.
When the ambient temperature Ta increases to 100 oC, luminous efficiencies (LEs) of amber and red LED suffer from 23% and 46% decreases of those at 10 oC, respectively. The results is in agreement with the previous literature, experimentally validated the output power decreases by increasing ambient temperature . This
phenomenon can be attributed to two reasons: (1) In viewpoint of spectral characteristics, the SPDs of amber and red color would shift to longer wavelength at high ambient temperature Ta, resulting in the decreases of luminous efficiency . (2) In terms of material, for the AlInGaP-based LEDs, due to the carrier overflow by increased ambient temperature, the luminous efficiency would be reduced accordingly
.
Figure 4-9. The temperature dependence of LE for pentachromatic LEDs. When Ta is varied from 10 oC to 100 oC, LEs of amber and red AlInGaP LEDs decrease to 23% and 46% of that at 10 oC while LEs of InGaP LEDs are insensitive to temperature variation.
4.2.2 Spectral modulation with thermal compensation
In order to compensate the drift caused by thermal effects, the proposed optimization methodology shall be applied to different ambient temperatures in the first place. Thus a table of drive current versus ambient temperature can be preloaded to the cluster system for practical operation. Table 4-1 shows the example that summarizes the compensation outcomes for the extreme T of 10 oC and 100 oC.
Table 4-1. The comparison of CQS, LE, output luminous flux Φv, correlated color temperature CCT, color temperature CT and the input power ratio Pin under Ta = 10oC, 50oC and 100oC.
100oC
* Simulation without compensation ** Simulation with compensation
*** Measurement result
It is observed that the technique effectiveness is fully applied for the predefined requirements in smart lighting: high color quality scale (above 85 points), high luminous efficiency (above 100 lm/watt) over a wide range of color temperature (CT
= 2800-8000K). The thermal compensation technique works with wide chromaticity locus and, in particular, it is proven to work with low color temperature noticeably influenced by thermal variation. Taking case I (CT = 3200K) as an example, as the ambient temperature Ta changes from 10 oC to 100 oC, the power ratio of dominant red channel changes from 28% to 44%. This modulation is predictable because the decreased luminous efficiency LE of the dominant field (red color) follows the raise of the ambient temperature. In order to keep the chromaticity point, we must extract more luminous flux from the red majority and thus more power ratio (Pin) is required
The consequence can be deduced in other operational conditions. As the lighting is operation at high color temperature (CT > 4600K), phosphor-converted white source is the dominant field (over 50%) due to its unique characteristics of high luminous efficiency and dully dependence upon the thermal effects. Therefore, in case of operation in high color temperature (CT), we suggest a scenario as following: (1) utilize phosphor-converted white source as a dominant field, accompanied by a small amount of other complementary single-color to keep the light quality and the adjustable chromaticity, (2) replace single red or amber emitter by two or more devices with less drive current, and thus reduce the thermal effect and enhance the entire cluster efficiency, (3) replace amber AlInGaP LED by phosphor-converted amber with higher flux density and better color stability .
4.2.3 Optimized pentachromatic LEDs cluster
In sum, Figure 4-10 shows the contour map of possibly highest luminous efficiency LE subject to predefined requirements (CQS > 85 points, high luminance level 100 lm
and negligible color deviation Δxy < 0.01 ). With different operational ambient temperatures, it’s not likely to reach high efficiency at high ambient temperatures. The best performance (LE > 130 lm/watt) lies in a narrow region about CT = 4000 − 6500K associated with self-evident low ambient temperature (Ta =10 oC ~ 20 oC). If the luminous efficiency LE = 100 lm/watt is settled as the minimum requirement, a full operable range for ambient temperature Ta can be workable only within the high color temperature range CT > 5200K.
Figure 4-10. The LE contour of the pentachromatic LEDs cluster is performed under the predefined requirements (CQS> 85 points, lighting level =100 lm and Δxy < 0.01). When the LE = 100 lm/watt is selected as the minimum efficiency boundary, a full operation range for ambient temperature can be obtained for CT >
5200K.
4.3 Summary and conclusions
The proposed multispectral mixing scheme has been individually realized into two examples aimed for general lighting application. In the case of low power LEDs cluster, the SPD can be assumed to be thermal-independent. The composed spectra have been experimentally verified for different color temperatures and operation modes.
According to the comparison of the R/G/B and R/G/B/A system, we found that the system including amber source could have the average improvement of 50% in color quality scale CQS could without too much loss of luminous efficiency LE. In addition, it is better to operate the R/G/B/A cluster at the high color rendering mode (i.e. the weight factor ~ 1) with the analyzed result of CQS and LE , while the
stringent operable range in color temperature still preclude its use in general lighting.
A hybrid design has therefore been proposed. The addition of cold-white (CW) LED to R/G/B/A system enables a further improvement to both CQS and LE, leading to an extended operation window from 2600K to 8500K. Thus a low power color tunable system can be accomplished.
For the case of high power LEDs cluster, the thermal effect and its influence on the chromaticity point have been analyzed. With the raise of the ambient temperature, the drift of chromaticity point can be mainly attributed to the decreased luminous efficiencies of amber and red sources. By applying the proposed optimization methodology in advance, we can produce a compensation mechanism against the whole range of ambient temperature. The effectiveness of the developed technique has been proven as the outcome in Table 4-1. Therefore, a color-tunable high power LEDs cluster can have wider temperature operation range in practical use.
Chapter 5
Conclusions and Future Works
5.1 Conclusions
The conclusions for this dissertation research are summarized as follows:
5.1.1 LED Spectral Characterization
1. The characterization is aimed to obtain the dependence between the input digital count (or drive current) and the output spectral power distribution of a LED.
Because the resistance of a LED is highly affected by the thermal effect, in the first part of the thesis, we conducted a sequence of measurements to obtain the data base of voltage-temperature dependence subject to different drive current.
2. With the sufficient amount of sampling measured data, we could have the relation of junction temperature with respect to DC drive current and ambient temperature, as developed by A. Keppens [Equation (2-6)]. In that case, we can easily save the computational complexity; all the input and corresponding variables can be attributed by a single parameter: drive current.
3. In order to estimate the behavior of spectral power distribution with the reduced dimension, we approximate the SPD by Gaussian fitting, where three parametric features: peak wavelength, intensity and spectral width are functions of drive current and ambient temperature, respectively. The resultant SPD can be
represented as a form of Equation (2-12). In terms of primary-based LED, a double Gaussian approximation is sufficient to estimate its SPD with high accuracy. On the other hand, for phosphor-based LED, the SPD of excitation source and phosphor shall be approximated by individual double Gaussian forms.
5.1.2 Multispectral Optimization as Lens Design Techniques
1. To optimize the SPD of a LED cluster according to different operational purposes, we proposed a novel methodology, which can be conceptually analogous to the general lens design rule that has long been developed in past few decades.
2. The proposed methodology is based on an assumption that the thermal status
2. The proposed methodology is based on an assumption that the thermal status