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Standalone low-voltage DC (LVDC) microgrids have emerged as potential alternatives in the context of effective rural electrification. The factors of reduction in conversion costs, paradigm shift in voltage levels of domestic loads made LVDC Microgrids more preferable. Being driven by intermittent renewable sources and dynamic loading, the voltage control is quite crucial and challenging to ensure a stable LVDC microgrid. Furthermore, delivering the control objectives becomes very difficult in the presence of sensor faults. In order to address this issue of sensor faults, this work proposes an Extended Luenberger Observer-based Active Sensor Fault-Tolerant Control (ELO-ASFTC) scheme. The proposed control scheme consists of the aspects of fault detection and isolation (FDI), and control reconfiguration. The proposed control scheme achieved the voltage tracking objective of the LVDC microgrid even under the presence of a faulty DC bus voltage sensor. The performance of the proposed scheme is observed in handling different sensor fault scenarios, loading conditions and irradiance changes. The effectiveness of the proposed control scheme is studied analytically, through the simulation studies in MATLAB, and hardware experimentation on the in house LVDC microgrid test bed. [ABSTRACT FROM AUTHOR]

A prior prediction of oxides of nitrogen, i.e., NOX (sum of NO and NO2), in diesel exhaust while treating with electric discharge-based nonthermal plasma (NTP) technique, would assist the researchers in planning the resources required for the treatment. In this present study, the performance of different regression-based models, i.e., linear, support vector regression and Gaussian process regression (GPR), has been analyzed for predicting the NOX concentrations based on the values of five dominating parameters of the NTP treatment. Experiments have been conducted and collected a dataset of 4032 number of input–output pairs to be used for training and testing of the regression models. The performances of these models have been assessed while testing them for the unseen set of data. A comparison of root-mean-square error (RMSE) has been made, where Matern 3/2 type of GPR model has been found to be the best among all the considered models with an RMSE of 1.86 ppm for a test data of 1210 sets. The model is shown to perform consistently well even when the test data are increased to 50% of total data. Regression analysis shows that the NOX can be predicted with very good accuracy using the Matern 3/2 type of GPR model. [ABSTRACT FROM AUTHOR]

A prior prediction of voltage required for the nonthermal plasma (NTP)-based diesel exhaust treatment toward removal of nitrogen oxides, i.e., NOX (sum of NO and NO2) would help the researchers to plan for the resources required for the treatment. In this present study, experimental data set of 4032 number of input-output pairs have been collected by taking flow rate (Fr), temperature (T), discharge gap (Dg), initial NOX concentration (NOXi), and NOX removal efficiency (ηr) as the 5 inputs and the voltage required for the treatment (Vrt) as the output. Then, an attempt has been made to predict Vrt for achieving particular ηr, while other input parameters have fixed values, using multivariable linear and quadratic polynomial regression techniques. The performances of these two predictive models have been assessed during training and testing. The root mean square error (RMSE) between experimental and predicted values of Vrt with both the models has been compared, where quadratic polynomial regression-based model has been found to be performing well with an RMSE of 0.85 kV for a test data of 1210 sets. This study shows that the voltage required for the treatment, to achieve a particular amount of NOX removal from the exhaust, can be predicted with very good accuracy so that the necessary arrangements for the treatment can be made by the researchers. [ABSTRACT FROM AUTHOR]

High-voltage discharge-based nonthermal plasma (NTP) treatment for diesel exhaust is a laboratorial proven efficient technique. A prophecy of the treatment results based on the knowledge of its parameters would be a step forward toward bringing it into real-time applications of pollution control. In this paper, artificial neural networks (ANNs) and fuzzy logic model (FLM) have been used to model the NO $_{ X }$ (sum of NO and NO2) concentrations as a function of parameters of the NTP process. A data set of 4032 input–output pairs has been collected by conducting experiments, in which 70% of the data are used for the training of the models derived. The performances of all the considered models have been evaluated by testing them for the remaining 30% of the data, which is novel for the models. Furthermore, a comparison of the models has been made based on the root-mean-square error (RMSE) and mean relative error (MRE), where the FLM has been found to be the better compared to the ANN-based models, i.e., ANN, multilayer perceptrons (MLP), and functional link ANN (FLANN). The RMSE of FLM is 2.53 ppm for a test data of 1210 sets. It can be said from these results that the NO $_{ X }$ concentrations can be predicted using FLM with a good accuracy. [ABSTRACT FROM AUTHOR]

Application of the nonthermal plasma (NTP) technology for NOX removal from diesel engine exhaust has already been experimentally proved to be an efficient method at laboratory level. The NOX removal efficiency depends on various electrical and physical parameters, and very few studies have been carried out to predict it with the variation in those parameters. In this paper, an approach has been made using dimensional analysis to predict the NOX concentration with the NTP treatment, based on its dependence on various operating parameters. A relation has been obtained between NOX concentration and 11 numbers of parameters affecting NOX removal so as to form dimensionless groups. A mathematical model has been established using the experimental data and nonlinear regression technique. Experiments are conducted to validate this model with variations in the parameters voltage, flow rate, temperature, discharge gap width, and initial NOX concentration. The predicted NOX concentration values have been found to be well matched with the experimental results. The rms errors for the test data are found to be 4.64%, and in ppm, it is 9.58. [ABSTRACT FROM AUTHOR]

The research work in this paper is based on generation of high voltage pulses using compact power supply sources for abatement of NOX from the diesel engine exhaust. The high voltage source is made up of zero voltage switch cascaded with flyback converter to produce high voltage AC, a Cockroft-Walton voltage multiplier to generate high voltage DC and a rotary spark gap for the production of high voltage pulses of rise time in the range of nano seconds. The rectifier based power supply is validated by a 12 V battery supply. To corroborate the feasibility of proposed methodology in diesel operated vehicles, the experiments are conducted with a 12 V battery. Performance of various shapes of electrodes (cylindrical 5mm diameter, square 5 mm diagonal and hexagonal with vertex to vertex diameter of 5 mm) at different flow rates of 2 l/min, 4 l/min and 6 l/min are also examined. [ABSTRACT FROM PUBLISHER]

With ever more stringent \NOX emissions, it is necessary to examine removal of nitrogen oxide from diesel engine exhaust. This paper describes the study of \NOX reduction from 5.9-kW stationary diesel engine exhaust under nanosecond pulse energization. Two plasma reactors characterized by dielectric barrier discharge has been designed, built, and evaluated. One of the reactor designs include nine numbers of electrodes kept in parallel, and the exhaust was allowed to pass axially, whereas the second reactor consists of nine parallel electrodes and the exhaust was allowed to pass radially. The reactors were individually tested for the treatment of nitrogen oxides for gas flow rate of 2, 5, and 10 L/min. Both the reactors have been individually tested, and results show an appreciable removal of \NOX with equal discharge volume. From the results, it was found that both the reactors were an efficient \NOX removal. With consumption of only 36 J/L, the reactors had shown a considerable 45% \DeNOX efficiency. [ABSTRACT FROM AUTHOR]

Red mud is a waste by-product generated during the processing of bauxite, the most common ore of aluminium. With the presence of ferric oxide, high surface area, resistance to poisoning and low cost, red mud made itself a good alternative to the existing commercial automobile catalyst. The cascading of dielectric barrier discharge plasma with red mud improved the NOX removal from diesel engine exhaust significantly. The DeNOX efficiency with discharge plasma was 74% and that with red mud was 31%. The efficiency increased to 92% when plasma was cascaded with red mud catalyst operating at a temperature of 400°C. The NOX removal was dominated by NO2 removal. The studies were conducted at different temperatures and the results were discussed. [ABSTRACT FROM AUTHOR]

In this paper studies were carried out on two compact electric discharge plasma sources for controlling nitrogen oxides (NOX) emission in diesel engine exhaust. The plasma sources consist of an old television flyback transformer to generate high frequency high voltage ac (HVAC) and an automobile ignition coil to generate the high voltage pulses (HV Pulse). The compact plasma sources are aimed at retrofitting the existing catalytic converters with electric discharge assisted cleaning technique. To enhance NOX removal efficiency cascaded plasma-adsorbent technique has been used. Studies were reported at different flow rates and load conditions of the diesel engine. [ABSTRACT FROM PUBLISHER]

In this paper, a different type of cross flow dielectric barrier discharge (DBD) reactor was designed and tested. Here the gas flow is perpendicular to the barrier discharge electrode. Discharge plasma was utilized to oxidize NO contained in the exhaust gas to NO2 and subsequent NO2 removal can be improved using an adsorbent system. A detailed study of DeNOX in a stationary diesel engine exhaust was carried out using pulsed electrical discharges/adsorbent processes. Activated alumina (Al2O3) and MS-13x were used as adsorbents at room temperature. The main emphasis is laid on the removal of NOX from the filtered diesel engine exhaust. In filtered exhaust environment, the cross flow reactor along with adsorbent exhibits a superior performance with regard to NOX removal when compared to that with axial flow of gas. In this paper we bring out a relative comparison of discharge plasma and plasmaadsorbent process at various gas flow rates, ranging from 2 l/min to 25 l/min. The discharge plasma-adsorbent assisted barrier discharge reactor has shown promising results in NOX removal at high flow rates. [ABSTRACT FROM PUBLISHER]