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Linear switched reluctance motors are a focus of study for many applications because of their simple and sturdy electromagnetic structure, despite their lower thrust force density when compared with linear permanent magnet synchronous motors. This study presents a novel linear switched reluctance structure enhanced by the use of permanent magnets. The proposed structure preserves the main advantages of the reluctance machines, that is, mechanical and thermal robustness, fault tolerant, and easy assembly in spite of the permanent magnets. The linear hybrid reluctance motor is analyzed by finite element analysis and the results are validated by experimental results. The main findings show a significant increase in the thrust force when compared with the former reluctance structure, with a low detent force.

A previous article has presented the members of the asymmetrical interleaved dc/dc switching converters family as very appropriate candidates to interface between photovoltaic or fuel cell generators and their loads because of their reduced ripple and increased current processing capabilities. After a review of the main modeling methods suitable for high-order converters operating, as the asymmetrical interleaved converters (AIC) ones, in discontinuous current conduction mode a full-order averaged model has been adapted and improved to describe the dynamic behavior of AIC. The excellent agreement between the mathematical model predictions, the switched simulations and the experimental results has allowed for satisfactory design of a linear-quadratic regulator (LQR) in a fuel-cell application example, which demonstrates the usefulness of the improved control-oriented modeling approach when the switching converters operate in discontinuous conduction mode.

This paper studies a Hybrid Renewable Energy System (HRES) as a reliable source of the power supply in the case of the connection to the grid. The grid connection imposes restrictions to the power delivered and harmonic content on the HRES. This causes the HRES to use multiple control systems and subsystems, as the normalization of the measurements, the current control, active harmonic compensation, synchronization, etc., described in this paper. Particular attention was paid to interactions in the storage system of the HRES. The durability of the HRES can be increased by the combination of the supercapacitors and batteries. This requires a power management solution for controlling the energy storage system. The aim of the supercapacitors is to absorb/inject the high-frequency fluctuations of the power and to smooth out the power of the batteries system of the HRES. This can be possible owing to the use of a low-pass second order filter, explained in this paper, which separates the high-frequency component of the storage system reference for the supercapacitor from the low-frequency component for the batteries system. This solution greatly increases the reliability and durability of the HRES.

Automated guided vehicles (AGV) or mobile robots (MR) are being used more and more in modern factories, logistics, etc. To extend the work-time of the robot, kinetic energy recovery systems are implemented to store the braking or lifting energy. In most applications, the energy storage system is a Li-ion battery, which is therefore subjected to increased stress and is also oversized. Super-Capacitors can be used in combination to solve this issue. In this paper, different power distribution systems are analysed and compared, using both single or hybrid storage systems (battery and super-capacitor combined). The comparison is both qualitative, using general system characteristics, and quantitative, using an efficiency/power density Pareto front analysis.

This paper presents a comprehensive approach to analyze and design the voltage and current loops of switching DC-DC converters by using sliding-mode control theory. The approach is interchangeably applied to switching converters under current-programmed control with both fixed and variable frequency modulation. An ideal sliding-mode dynamics model is then obtained together with its circuit schematic representation that can be used for designing the output voltage compensator, as well as to predict the large signal behavior such as during start-up and under large disturbances. Simulations and experimental measurements illustrate the theoretical approach for two different examples of switching converters.

In many countries, Heavy Fuel Oil (HFO) is still a common fuel in industrial applications due to its low price and high energy density. However, the complex and incomplete combustion of HFO results in high levels of emissions and low efficiency, which causes the search for additives to improve its properties without affecting its heating value. The present paper aims to use as an additive the liquid fraction from pyrolysis of the polystyrene for fuel oil, replacing conventional additives such as cutter stock, improving its fluidity without using heat to pump it. As for pyrolysis for obtaining pyrolytic oil, the effect of temperature on the chemical composition of the liquid fraction from the thermal pyrolysis of compact polystyrene was studied. PS pyrolysis was carried out in a temperature range between 350 to 450 °C at a heating rate of 15 °C min−1 in a batch type reactor, with a condensation system, in order to analyze the best fraction liquid yield. At 400 °C we obtained a liquid fraction of 81%. This product presented a kinematic viscosity of 1.026 mm2 s−1, a relative density of 0.935, a flash point of 24 °C, and a gross heating value of 48.5 MJ kg−1. Chromatographic analysis indicates that 75% by mass of the components corresponds to C6 to C20 hydrocarbons, showing the high generation of isomers of the polystyrene monomer and aromatic compounds. The product obtained is mixed with base fuel oil at 60 °C at 250 rpm for a period of one hour, in percentages of 10 to 50% by mass. The 10% mixture has properties very close to those required by the standard fuel oil, presenting a viscosity of 108 mm2 s−1 that adjusts to the requirements in burners for industrial applications; additionally, it has a Sulphur content lower than that of fuel oil without affecting its heating value.

In this study, ammonia vapor absorption with NH3/LiNO3 was assessed using correlations derived from a semi-empirical model, and artificial neural networks (ANNs). The absorption process was studied in an H-type corrugated plate absorber working in bubble mode under the conditions of an absorption chiller machine driven by low-temperature heat sources. The semi-empirical model is based on discretized heat and mass balances, and heat and mass transfer correlations, proposed and developed from experimental data. The ANN model consists of five trained artificial neurons, six inputs (inlet flows and temperatures, solution pressure, and concentration), and three outputs (absorption mass flux, and solution heat and mass transfer coefficients). The semi-empirical model allows estimation of temperatures and concentration along the absorber, in addition to overall heat and mass transfer. Furthermore, the ANN design estimates overall heat and mass transfer without the need for internal details of the absorption phenomenon and thermophysical properties. Results show that the semi-empirical model predicts the absorption mass flux and heat flow with maximum errors of 15.8% and 12.5%, respectively. Maximum errors of the ANN model are 10.8% and 11.3% for the mass flux and thermal load, respectively.