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Abstract This paper deals with an optimization of the Stirling engine regenerator’s. Firstly, different materials are experimented (Stainless Steel, Copper, aluminum and Monel 400). The engine performances and the state of each material after 15 h of use are considered. The Stainless steel was the material that best satisfies these two conditions. Five regenerators in stainless steel with different porosities were manufactured and experimented (95%, 90%, 85%, 80% and 75%). Porosity that gives the best trade-off between maximizing the engine brake power, maximizing the heat transfer and minimizing the pressure drops, was retained. Thus, the regenerator in stainless steel with porosity of 85% was considered as the most suitable matrix maximizing the Stirling engine performances and minimizing heat and friction losses.

This paper proposes a data-driven diagnostic approach for Polymer Electrolyte Membrane Fuel Cell (PEMFC) systems. Fault detection and isolation (FDI) is realized by analyzing individual cell voltages. A feature extraction method Fisher Discriminant Analysis (FDA) and a multi-class classification method Directed Acyclic Graph Support Vector Machine (DAGSVM) are utilized successively to extract the useful features from raw data and classify the extracted features into various classes related to health states. Experimental data of two different stacks are used to validate the proposed approach. The results show that five concerned faults can be detected and isolated with a high accuracy. Moreover, the light computational cost of the approach enhances the possibility of its online implementation.

Abstract The aim of this paper is to present a design tool with its guiding principles for energy conversion and noise characterization of an exterior rectangular duct often installed on building envelopes for pre-conditioning of fresh air. The energy conversion in an exterior rectangular duct is a function of solar irradiation, air gap width, mass flow rate and pressure, wall and air temperatures. A generalized two dimensional thermal analysis of an outdoor duct is presented by placement of surface and air nodes into two adjacent stacks of control volumes representing outer and inner walls of duct. A matrix solution procedure is adopted by constituting conjugate heat exchange of conduction, convection, radiation and ventilation heat transport. The rectangular duct model is built by a metallic exterior wall exposed to a steady heat flux generation due to solar heat gain and a well-insulated back panel as its counterpart wall. The model improves the results of traditional thermal models for the cases where: (i) there are sections of conjugate heat exchange; and (ii) stack effect due to thermal buoyancy necessitates 2-D nodal analysis for distant composite nodes. The design tool is supported with some numerical and experimental results of an airflow window with a photovoltaic (PV) solar wall installed in an outdoor test-room. Furthermore, some examples of noise characterization calculations are illustrated using devised noise measurement equations.

Abstract As an alternative to thermoelectric generators, heat engines show great interest thanks to their ability to convert temperature spatial gradient into time-domain temperature variations or vibrations. To this end, MultiPhysic Memory Alloys (MPMAs), combining shape memory characteristics with ferromagnetic properties, provide significant attractive characteristics such as sharp transition with reduced hysteresis as well as magnetic properties enabled by heating, thus allowing easier device development and implementation. In this study, we report the development of a heat engine for small-scale energy harvesting where the MPMA transfers its heat to a pyroelectric element that provides thermal to electrical energy conversion, yielding a more direct energy conversion path compared to conventional electromechanical heat engines. Furthermore, thermally decoupling the pyroelectric element from the MPMA allows a faster cooling of the latter, accounting for higher variation frequency. Compared to the use of electromagnetic transduction through a coil attached to the moving MPMA, this approach is shown to provide 3 to 9 times more power density (according to considered volume), with theoretical potential gains from 8 to 25 with the use of nonlinear electrical interfaces.

Abstract This paper introduces a new switching means giving a real time optimum connection mode of domestic appliances on either the electrical grid or a photovoltaic panel (PVP) output. A fuzzy algorithm makes the decision which ensures the optimal energy-management based on PVP generation and appliances states with respect to energy-saving criteria. Validation is driven on a 1 kW peak (kWp) PVP and domestic appliances of different powers installed at the Energy and Thermal Research Centre (CRTEn) in the north of Tunisia. Results confirm that energy saved during daylight is 80–90% of the PVP generated energy.

The evolution of temperatures in internal combustion engines during cold start is quite important. This greatly affects fuel consumption and vehicle emissions. In this paper, an advanced thermal management model is presented and used on an automotive Diesel engine in order to determine the evolution of the different temperatures during warm-up stage. The paper focuses on the complete description of the engine components, coolant circuit, and lubricant circuit. The objective is to calculate the heat exchanges between the thermal masses of sub-models (cylinder head, engine block, pistons, oil sump…) and the fluids. Experiments on an engine were realized in order to calibrate the model (heat release, friction losses…) but also to obtain the temperature evolutions during transient stage. These last results were used in order to validate the model. This approach gives the possibility to determine the coolant and oil temperature evolution with a minimum of nodes and a relatively short calculation time. The evolution of the coolant temperature in a vehicle during a NEDC cycle with a cold start was studied. A good agreement was obtained. Finally, the model was used in order to study the possibilities to reduce the vehicle mass by a reduction of the engine mass.

Energy systems at district/urban level are getting more complex and diversified from time to time. Different energy carriers are coupled each other to meet various types of energy demands. The conv ...

Abstract The statistical study of wind speed measurements on a site makes it possible to determine a distribution law, needed to assess the available or recoverable wind energy potential. The classical approach consists in assimilating the distribution law to standard models, for example Weibull or Rayleigh, and in determining the parameters of the model so that it gets closest to the discrete law obtained by statistically treating the wind speed measurements. The Weibull model is the most used one and provides good results. However, the accurate determination of the wind speed distribution law constitutes a major problem. Multi Layer Perceptron type artificial neural networks, highly effective in function approximation problems, are used here for the approximation of the wind speed distribution law. The site energy characteristics have been determined by means of the neural approach and compared with those obtained by the classical method. The results show that the distribution law achieved by the neural model provides assessments closer to the discrete distribution than the Weibull model. This approach has enabled the wind energy potential on the Dakar site to be determined in a more accurate way. The models are also used to assess the amount of energy the wind generator WES18 of 80 kW power, set up at 10 m and 40 m above the ground, would produce annually.