3,185 research outputs found
LC compensators for power factor correction of nonlinear loads
No full textThis material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. Copyright @ 2004 IEEEA method is presented for finding the optimum fixed LC compensator for power factor correction of nonlinear loads where both source voltage and load current harmonics are present. The LC combination is selected because pure capacitive capacitors alone would not sufficiently correct the power factor. Optimization minimizes the transmission loss, maximizes the power factor, and maximizes the efficiency. The performance of the obtained compensator is discussed by means of numerical examples
LC compensators based on transmission loss minimization for nonlinear loads
No full textThis material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. Copyright @ 2004 IEEEThis paper presents a method employing the penalty function search algorithm to determine the LC compensator value for the optimal power factor correction in nonsinusoidal systems. The objective of the proposed method is to minimize the transmission loss while the power factor and efficiency are taken as constraints and utilized in order to solve the multiobjective optimization problem by transforming it into a single objective one. Examples show that the load nonlinearity can have a significant impact on optimal compensator sizes
Cost-effective applications of power factor correction for nonlinear loads
No full textThis material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. Copyright @ 2005 IEEEThe objective of this paper is to propose a new approach for designing passive LC compensators by using the penalty function method as an optimization tool. The performance of the cost-effective passive LC compensator for a constant load depends on the appropriate inductor and capacitor selection. Several design methods are reviewed and a novel design methodology is proposed in this paper. By using the proposed method, the designer can quickly find appropriate parameter values to meet the desired circuit performance. Simulated results show that an appropriate combination of the inductor and capacitor selected by the proposed method can meet the desired power-quality requirement. Different cases of design examples are shown in this paper to verify the performance of the proposed design methodology
A 155W −95.6 dB THD+N GaN-based Class-D Audio Amplifier With LC Filter Nonlinearity Compensation
No full textSilicon MOSFETs-based medium-power (< 50W) Class-D amplifiers (CDAs) switching in the MHz range have gained popularity in recent years, which achieves better linearity thanks to a higher loop gain in the audio band while enabling the use of LC filters with higher cut-off frequencies. However, for high-power (>100 W) CDAs, such switching frequency and high load current could lead to significant power loss. Furthermore, in the presence of a large current and voltage applied to the load, the linearity of the system can quickly degrade due to LC filter component voltage/current dependency. Without any LC filter nonlinearity compensation technique, LC components with high voltage/current rating must be used to reach high system linearity, which are often expensive and bulky. This paper presents a CDA using a GaN-based output stage to achieve high switching frequency and good efficiency simultaneously, and an integrated controller implemented in a 180nm CMOS technology to compensate for the LC filter nonlinearity. Switching at 1.8 MHz, the CDA can deliver a maximum of 155W from a 50V supply into a load with a peak efficiency of 91.7%. It achieves a peak THD+N of −95.6 dB (0.0017%) while allowing the use of cheaper and smaller nonlinear LC components.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Electronic Components, Technology and MaterialsMicroelectronic
A - 121.5-dB THD Class-D Audio Amplifier With 49-dB LC Filter Nonlinearity Suppression
No full textClass-D audio amplifiers produce electromagnetic interference (EMI), which often needs to be suppressed by an external LC filter. However, due to component nonlinearity, this filter can itself cause significant distortion. This article presents a class-D amplifier that suppresses LC filter nonlinearity by 49 dB and is robust to ±30% variations in its cutoff frequency. This is achieved by a dual-loop architecture, in which an inner loop provides stability, while an outer loop provides the high gain needed to suppress the LC filter and output-stage nonlinearity. A prototype, implemented in a 180-nm BCD process, achieves -121.5-dB total harmonic distortion (THD) and -107.1-dB THD+N, which is maintained to within 3 dB even as the LC filter cutoff frequency is varied from 62 to 106 kHz. It can deliver a maximum of 21 W into a 4-Ω load with 87% efficiency and 12 W into an 8-Ω load with 91% efficiency, measured at 10% THD. Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Electronic InstrumentationMicroelectronic
Multichannel LC ADC: to Record Atrial Electrograms
No full textBiosignals such as electoencephalogram (EEG), electrocorticogram (ECoG), atrial electrogram (AEG) etc. are being recorded from multiple channels simultaneously to improve the spatial resolution of the signals. Conventional multichannel synchronous Analog-to-Digital Converters (ADCs) are used to convert the analog continuous time signals into discrete digital values. Several biosignals have a sparsity in time domain as they have fast-rising peaks in between periods of low activity. Use of conventional synchronous ADCs for conversion of such signals is not an efficient approach as their operation is constant, irrespectiveof the activity of the input signals. Asynchronous ADCs such as level-crossing (LC) ADCs exploit the sparsity of biosignals and thus their operation is activity-dependent. However, multichannel configurations of LC ADCs do not yet exist. This problem is investigated in this work and a new ADC architecture is presented that can combine synchronous sampling with level-crossing quantisation method while converting input signals from several channels simultaneously. The synchronous LC ADC presented in this work achieves 3.37 times reduction in quantisation steps and 6 times reduction in number of output bits generated during conversion of AEG signals as compared to conventional synchronous ADCs. The problem in existing LC ADCs of data overhead in adaptive resolution technique is solved through a novel method named split resolution technique which is also presented in this work.Electrical Engineerin
Practical considerations regarding power factor for nonlinear loads
No full textThis material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. Copyright @ 2004 IEEEThe choice of LC compensator may be constrained by the availability of manufacturers units. To account for this, the capacitor values are chosen from among standard values and for each value the transmission losses is minimized, or power factor is maximized, or transmission efficiency is maximized. The global minimum or maximum is obtained by scanning all local minims or maxims. The performance of the obtained compensator is discussed by means of numerical examples
A -91 dB THD+N Resistor-Less Class-D Piezoelectric Speaker Driver Using a Dual Voltage/ Current Feedback for LC Resonance Damping
No full textPiezoelectric speakers are gaining popularity on account of their improving form-factor and audio quality, making them a good fit for many audio applications such as in televisions, laptops, etc. Such speakers can be modelled as a large capacitive load, and so are typically driven by a Class-AB amplifier via a series resistor that ensures driver stability, and limits load current, but wastes power [1], [2]. In [3], the Class-AB amplifier is replaced by a more power-efficient Class-D amplifier (CDA) in series with an additional inductor. However, a series resistor is still required to damp the resulting LC resonant circuit, which could otherwise draw excessive currents when excited by large-signal distortion (e.g. clipping) harmonics around the LC resonance frequency. Alternatively, by using a feed-forward architecture based on LC filter diagnostics to limit overshoot currents, the series resistor can be replaced by a second inductor, at the expense of increased system complexity and cost [4].Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Electronic InstrumentationMicroelectronic
A-121.5 dB THD Class-D Audio Amplifier with 49 dB Suppression of LC Filter Nonlinearity and Robust to +/-30% LC Filter Spread
No full textThis paper reports a Class-D audio amplifier that uses multiloop feedback to suppress output LC filter nonlinearity by 49 dB, enabling the use of small, low-cost LC filters with ±30% spread while maintaining low distortion. Fabricated in a 180 nm BCD process, the prototype achieves a THD of-121.5 dB and a THD+N of-107.1 dB. It delivers 12W/21W into an 8-Ω/4-Ω load with 91%/87% efficiency.</p
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Examining the Effects of Linguistic Complexity on Emergent Bilinguals’ Academic Content Performance
No full textThis dissertation explored whether unnecessary linguistic complexity (LC) in mathematics and biology assessment items changes the direction and significance of differential item functioning (DIF) between subgroups emergent bilinguals (EBs) and English proficient students (EPs). Due to inconsistencies in measuring LC in items, Study One adapted a rubric counting instances of specific grammatical features in items and introduced a method for evaluating lexical features in items. Four raters were asked to count the presence of five grammatical features in assessment items and determine whether each feature contained construct-relevant vocabulary. The items were drawn from four content assessments administered to Massachusetts high school students: two biology assessments and two mathematics assessments. These counts of grammatical and lexical features were modeled in factor analyses to evaluate the multidimensionality of LC and subsequent fit of multidimensional LC models. While there were problems with raters consistently counting construct-irrelevant grammatical features, multidimensional models of LC fit acceptably well. Factor scores obtained from the measurement models for lexical complexity, relative clauses, and complex noun phrases created in Study One were used for Study Two. In Study Two, Rasch hierarchical generalized linear models (HGLMs) were created to evaluate DIF between different subgroups of EBs and EPs on a biology assessment and a mathematics assessment, as including LC as an item covariate may predict item responses differently by comparison group. Seven comparison groups were evaluated across two assessments (mathematics and biology): EPs versus EBs, EPs versus short-term EBs, EPs versus long-term EBs, short-term EBs versus long-term EBs, EPs versus Spanish-speaking EBs, EPs versus non-Spanish-speaking EBs, and non-Spanish-speaking EBs versus Spanish-speaking EBs (reference group versus focal group, respectively). For each comparison group, at least five models were created: a comparison model with all participants in the comparison group with that only accounts for the main effect of focal group status, a “base model” that evaluated DIF for the comparison groups with no LC item covariates, a model including lexical complexity as an item covariate (“LEX predictor”), a model including complex noun phrases as an item covariate (“NP predictor”), and a model including relative clauses as an item covariate (“RC predictor”). If LC predictor models improved model fit, models with multiple LC predictors were created.
For the EP versus EB comparison groups on the mathematics assessment, model fit only improved with the NP predictor model, while the LEX, NP, and RC predictor models improved model fit for the EB versus EB comparison groups; a model with all LC predictors improved model fit for the EB versus EB comparison groups. For the biology assessment, the LEX, NP, and RC predictor models improved model fit for all comparison groups; a model with all LC predictors improved model fit for all comparison groups. The main effects of the item covariates (LC factor scores) and their interactions with focal group status were evaluated, as were the number of items within a comparison group that had changes in DIF significance or direction when including a LC predictor. All LC predictors had consistent main effects across comparison groups. For the mathematics assessment, items with higher complex noun phrases factor scores were consistently more difficult for all comparison groups (NP predictor model), and items with higher lexical complexity (LEX predictor model, all predictors model) or relative clauses factor scores (RC predictor model, all predictors model) were consistently more difficult for all EB versus EB comparison groups. For the biology assessment and all comparison groups, items with higher lexical complexity (LEX predictor model, all predictors model) or complex noun phrases factor scores (NP predictor model, all predictors model) were consistently more difficult, and items with lower relative clauses factor scores (RC predictor model, all predictors model) were consistently more difficult, with one exception. In the all predictors models for the EB versus EB comparison groups, only relative clauses had a significant main effect.
There were some changes in interactions with LC predictors and focal group status. For the mathematics assessment and EP versus EB comparison groups, complex noun phrases interactions favored EPs. For the mathematics assessment and EB versus EB comparison groups, generally the interactions in the single LC predictor models generally favored STEBs compared to LTEBs and non-Spanish-speaking EBs compared to Spanish-speaking EBs, but when all LC predictors were included, no interactions between LC predictor and focal group status were significant. For the biology assessment and EP versus EB comparison groups, lexical complexity and complex noun phrases factor scores interactions generally favored EPs, and relative clauses factor scores interactions favored EBs and EB subgroups. For the biology assessment and EB versus EB comparison groups, regardless of whether examining the single LC predictor or all predictors models, no interactions between focal group status and LC predictor were significant.
Changes in DIF significance and direction were compared between the base model and LC predictor models for all comparison groups. For the mathematics assessment and EP versus EB comparison groups, after conditioning on complex noun phrases, items with complex noun phrases generally exhibited significant DIF favoring EBs, regardless of whether the complex noun phrases factor scores were high (one standard deviation above the mean) or low (due to floor effects, the lowest complex noun phrases factor score). For the biology assessment, all items exhibited significant DIF favoring EBs after accounting for lexical complexity, most items exhibited non-significant DIF after accounting for complex noun phrases or relative clauses, and items were mixed between exhibiting non-significant DIF or significant DIF favoring EBs after accounting for all LC predictors. While items with high relative clauses factor scores exhibited non-significant DIF, some items with low relative clauses factor scores exhibited significant DIF favoring EPs after accounting for relative clauses. Items with two or more high factor scores exhibited non-significant DIF, but items with two or more low factor scores exhibited significant DIF favoring EBs after accounting for all LC predictors. These results were fairly consistent across different EP versus EB comparison groups, although different items were flagged for DIF in initial models not accounting for LC predictors. Items were less difficult for EBs than EPs after accounting for LC features, which suggests the abilities of EBs are underestimated due to LC in items, even if the items have low LC. Considering subgroup differences in these EIRMs, the key takeaway is that while different items are flagged as exhibiting significant DIF for different EP versus EB comparison groups when examining DIF with no LC predictors, there are few subgroup differences in items changing DIF significance or direction after accounting for LC predictors
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