V-Transform: “An Enhanced Polynomial Coefficient Based DC Test for Non-linear Analog Circuits

Abstract—DC testing of parametric faults in non-linear analog circuits based on a new transformation, entitled, V-Transform acting on polynomial coefficient expansion of the circuit function is presented. V-Transform serves the dual purpose of monotonizing polynomial coefficients of circuit function expansion and increasing the sensitivity of these coefficients to circuit parameters. The sensitivity of V-Transform Coefficients (VTC) to circuit parameters is up to 3x-5x more than sensitivity of polynomial coefficients. As a case study, we consider a benchmark elliptic filter to validate our method. The technique is shown to uncover hitherto untestable parametric faults whose sizes are smaller than 10 % of the nominal values. I.

A Multilevel inverter structure with cascaded two level and three level inverters for IM drive with CMV elimination and DC link capacitor voltage balancing

Common mode voltage (CMV) variations in PWM inverter-fed drives generate unwanted shaft and bearing current resulting in early motor failure. Multilevel inverters reduce this problem to some extent, with higher number of levels. But the complexity of the power circuit increases with an increase in the number of inverter voltage levels. In this paper a five-level inverter structure is proposed for open-end winding induction motor (IM) drives, by cascading only two conventional two-level and three-level inverters, with the elimination of the common mode voltage over the entire modulation range. The DC link power supply requirement is also optimized by means of DC link capacitor voltage balancing, with PWM control, using only inverter switching state redundancies. The proposed power circuit gives a simple power bus structure.

Bi-directional Switch Commutation for a Resonant Matrix Converter supplying a Contactless Energy Transmission System

This paper describes a bi-directional switch commutation strategy for a resonant matrix converter loaded with a contactless energy transmission system. Due to the different application compared to classical 3 phase to 3 phase matrix converters supplying induction machines a new investigation of possible commutation principles is necessary. The paper therefore compares the full bridge series-resonant converter with the 3 phase to 2 phase matrix converter. From the commutation of the full bridge series-resonant converter, conditions for the bi-directional switch commutation are derived. One of the main benefits of the derived strategy is the minimization of commutation steps, which is independent from the load current sign.

AC Breakdown Characteristics of Epoxy Nanocomposites

Experiments were conducted to measure the ac breakdown strength of epoxy alumina nanocomposites with different filler loadings of 0.1, 1 and 5 wt%. The experiments were performed as per the ASTM D 149 standard on samples of thickness 0.5 mm, 1 mm and 3 mm in order to study the effect of thickness on the ac breakdown strength of epoxy nanocomposites. In the case of epoxy alumina nanocomposites it was observed that the ac breakdown strength was marginally lower for 0.1 wt% and 1 wt% filler loadings and then increased at 5 wt% filler loading as compared to the unfilled epoxy. The Weibull shape parameter (beta) increased with the addition of nanoparticles to epoxy as well as with the increasing sample thickness for all the filler loadings considered. DSC analysis was done to study the material properties at the filler resin interface in order to understand the effect of the filler loading and thereby the influence of the interface on the ac breakdown strength of epoxy nanocomposites. It was also observed that the decrease in ac electric breakdown strength with an increase in sample thickness follows an inverse power-law dependence. In addition, the ac breakdown strength of epoxy silica nanocomposites have also been studied in order to understand the influence of the filler type on the breakdown strength.

Predictive distribution modeling for rare Himalayan medicinal plant Berberis aristata DC

Predictive distribution modelling of Berberis aristata DC, a rare threatened plant with high medicinal values has been done with an aim to understand its potential distribution zones in Indian Himalayan region. Bioclimatic and topographic variables were used to develop the distribution model with the help of three different algorithms viz. GeneticAlgorithm for Rule-set Production (GARP), Bioclim and Maximum entroys(MaxEnt). Maximum entropy has predicted wider potential distribution (10.36%) compared to GARP (4.63%) and Bioclim (2.44%). Validation confirms that these outputs are comparable to the present distribution pattern of the B. atistata. This exercise highlights that this species favours Western Himalaya. However, GARP and MaxEnt's prediction of Eastern Himalayan states (i.e. Arunachal Pradesh, Nagaland and Manipur) are also identified as potential occurrence places require further exploration.

Coupling of High Voltage AC Power Line Fields to Metallic Pipelines

In the recent years, there has been a trend to run metallic pipelines carrying petroleum products and high voltage AC power lines parallel to each other in a relatively narrow strip of land. Due to this sharing of the right-of-way, verhead AC power line electric field may induce voltages on the metallic pipelines running in close vicinity leading to serious adverse effects. In this paper, the induced voltages on metallic pipelines running in close vicinity of high voltage power transmission lines have been computed. Before computing the induced voltages, an optimum configuration of the phase conductors based on the lowest conductor surface gradient and field under transmission line has been arrived at. This paper reports the conductor surface field gradients calculated for the various configurations. Also the electric fields under transmission line, for single circuit and double circuit (various phase arrangements) have been analyzed. Based on the above results, an optimum configuration giving the lowest field under the power line as well as the lowest conductor surface gradient has been arrived at and for this configuration, induced voltage on the pipeline has been computed using the Charge Simulation Method (CSM). For comparison, induced voltages on the pipeline has been computed for the various other phase configurations also.

Improved utilisation of an HF transformer in DC–AC application

Power conversion using high frequency (HF) link converters is popular because of compact size and light weight of highfrequency transformer. This study focuses on improved utilisation of HF transformer in DC–AC applications. In practical application, the operating condition of the power converter deviates significantly from the designed considerations. These deviating factors are commutation requirements (dead-time, overlap), mismatch in device drops and presence of the fundamental frequency in load current. As a result, the HF transformer handles some amount of low-frequency components (including DC) other than desired HF components. This causes the operating point in B-H curve to shift away from its normal or idealised position and hence results poor utilisation of the HF transformer and unwanted losses. This study investigates the nature of the problem with experimental determination of approximate lumped parameter modelling and saturation behaviour (B-H curve) of the HF transformer. A simple closed-loop control algorithm with online tuning of the controller parameters is proposed to improve the utilisation of the isolation transformer. The simulation and experimental results are presented.

Reinforcement learning with average cost for adaptive control of traffic lights at intersections

We propose for the first time two reinforcement learning algorithms with function approximation for average cost adaptive control of traffic lights. One of these algorithms is a version of Q-learning with function approximation while the other is a policy gradient actor-critic algorithm that incorporates multi-timescale stochastic approximation. We show performance comparisons on various network settings of these algorithms with a range of fixed timing algorithms, as well as a Q-learning algorithm with full state representation that we also implement. We observe that whereas (as expected) on a two-junction corridor, the full state representation algorithm shows the best results, this algorithm is not implementable on larger road networks. The algorithm PG-AC-TLC that we propose is seen to show the best overall performance.