Antonio Manuel Mateo García

A Simple 2-D Finite-Element Geometry for Analyzing Surface-Mounted Synchronous Machines With Skewed Rotor Magnets

We present a new 2-D FEM-based system for analyzing permanent-magnet surface-mounted synchronous machines with skewed rotor magnets. The system is based on generating a geometric equivalent non-skewed permanent-magnet distribution that accounts for the skewed distribution of the practical rotor. An appealing feature of the proposed system is that it can be easily performed in any 2-D electromagnetic FEM package by performing a simple change in the geometry of the magnets. Attributes of the method presented here include simplicity, high accuracy, low computational burden, and high speed compared to 3-D and 2-D multislice FEM analysis. Experimental results with both healthy and faulty machines corroborate the effectiveness of the model proposed in this work.

Load forecasting framework of electricity consumptions for an Intelligent Energy Management System in the user-side

This work presents an electricity consumption-forecasting framework configured automatically and based on an Adaptative Neural Network Inference System (ANFIS). This framework is aimed to be implemented in industrial plants, such as automotive factories, with the objective of giving support to an Intelligent Energy Management System (IEMS). The forecasting purpose is to support the decision-making (i.e. scheduling workdays, on-off production lines, shift power loads to avoid load peaks, etc.) to optimize and improve economical, environmental and electrical key performance indicators. The base structure algorithm, the ANFIS algorithm, was configured by means of a Multi Objective Genetic Algorithm (MOGA), with the aim of getting an automatic-configuration system modelling. This system was implemented in an independent section of an automotive factory, which was selected for the high randomness of its main loads. The time resolution for forecasting was the quarter hour. Under these challenging conditions, the autonomous configuration, system learning and prognosis were tested with success.

Influence of laser cutting on the fatigue limit of two high strenght steels

Laser cutting is widely used in the metal industry, particularly when components of high strength steels sheets are produced. On the other hand, the roughness of cut - edges produced by laser differs from that obt ained by other methods, such as mechanical blank ing, and this fact influence s the fatigue performance. Moreover, thermal effects are another factor to consider. In the present investigation, specimens of two grades of high strength austenitic steels were cut by laser and tested in the high cycle fatigue regime to determine their corresponding fatigue limits. One of the steels was a metastable stainless grade (AISI 301LN) whereas the other corresponded to the TWIP family (TWIP17Mn). Load control fatigue te sting was conducted at a stress ratio R of 0.1 and using the stair - case methodology. A series of fatigue specimens were tested without polishing the cut - edges and other s eries after a careful polishing, in order to assess the influence of the cut - edges con dition. R esults indicate a significant influence of the edges roughness, more marked for the AISI 301LN than for the TWIP steel. In the latter material, the presence of nitrides induced a premature fatigue crack nucleationAbstract Laser cutting is widely used in the metal industry, particularly when components of high strength steel sheets are produced. However, the roughness of cut edges produced by laser differs from that obtained by other methods, such as mechanical blanking, and this fact influences the fatigue performance. In the present investigation, specimens of two grades of high strength austenitic steels, i. e. AISI 301LN and TWIP17Mn, were cut by laser and tested in the high cycle fatigue regime to determine their corresponding fatigue limits. A series of fatigue specimens were tested without polishing and other series after a careful polishing of the cut edges, in order to assess the influence of the cut edges condition. Results indicate a significant influence of the edge roughness, more distinctive for AISI 301LN than for TWIP steel.

Evaluation of the bulk and alpha-case layer properties in Ti-6Al-4V at micro- and nano-metric length scale

In the present study the hardness of individual alpha ( )-Ti grains in Ti-6Al-4V was measured by nanoindentation using Berkovich tip indenter. Additionally, alpha-case layer was induced by performing isothermal heat treatment at 700 °C in air for 500 hours. The average hardness of the -Ti grains found in the bulk material and in the alpha-case layer were 6.7 ± 0.7 GPa and 9.4 ± 1.4 GPa, respectively. The high hardness of the -Ti grains in the alpha-case layer is due to solid solution strengthening caused by interstitial oxygen diffusion. The thickness of the developed alpha-case layer was estimated metallographically and compared with that measured from a hardness profile performed along the layer. Moreover, electron back-scattered diffraction was used to determine the local crystallographic orientation, the texture of the alloy microstructure, as well as phase fraction changes, where the nanoindentation measurements were performed.

Dynamic nonlinear reluctance network analysis of five phase outer rotor BLDC machine

This paper presents a dynamic reluctance network (RN) magnetic equivalent circuit (MEC) analysis of a 55/52-pole five phase outer rotor brushless direct current (BLDC) motor. Winding distribution, stator slotting and iron saturation is included in the model. With this analysis the dynamic characteristics of the tested machine can be calculated. Back EMF and cogging torque responses are compared with the ones obtained from the finite element model (FEM) under no load and load conditions. The computation time of the RN network is significantly low with respect to the FEM analysis. The experimental setup results turn to be in very close matching to those provided by the elaborated models.

Martensitic transformation during fatigue testing of an AISI 301LN steel

The plastic deformation accumulated during fatigue testing can induce the transformation of austenite to martensite in metastable austenitic stainless steels. To analyze this issue, a metastable austenitic stainless steel grade AISI 301 LN was studied in two different conditions, i.e. annealed and cold rolled. In the first case, the steel was fully austenitic, whereas cold rolled material had almost 30% of martensite. High cycle fatigue tests at a stress ratio of 0.8 were carried out on flat specimens from both steel conditions. Several characterization techniques, including optical microscopy, X-ray diffraction (XRD) and electron back scattered diffraction (EBSD), were used to detect and quantify the martensite induced by the cyclic deformation.The plastic deformation accumulated during fatigue testing can induce the transformation of austenite to martensite in metastable austenitic stainless steels. To analyze this issue, a metastable austenitic stainless steel grade AISI 301 LN was studied in two different conditions, i.e. annealed and cold rolled. In the first case, the steel was fully austenitic, whereas cold rolled material had almost 30% of martensite. High cycle fatigue tests at a stress ratio of 0.8 were carried out on flat specimens from both steel conditions. Several characterization techniques, including optical microscopy, X-ray diffraction (XRD) and electron back scattered diffraction (EBSD), were used to detect and quantify the martensite induced by the cyclic deformation.

Martensitic transformation during fatigue testing of an AISI 301LN stainless steel

The plastic deformation accumulated during fatigue testing can induce the transformation of austenite to martensite in metastable austenitic stainless steels. To analyze this issue, a metastable austenitic stainless steel grade AISI 301 LN was studied in two different conditions, i.e. annealed and cold rolled. In the first case, the steel was fully austenitic, whereas cold rolled material had almost 30% of martensite. High cycle fatigue tests at a stress ratio of 0.8 were carried out on flat specimens from both steel conditions. Several characterization techniques, including optical microscopy, X-ray diffraction (XRD) and electron back scattered diffraction (EBSD), were used to detect and quantify the martensite induced by the cyclic deformation.The plastic deformation accumulated during fatigue testing can induce the transformation of austenite to martensite in metastable austenitic stainless steels. To analyze this issue, a metastable austenitic stainless steel grade AISI 301 LN was studied in two different conditions, i.e. annealed and cold rolled. In the first case, the steel was fully austenitic, whereas cold rolled material had almost 30% of martensite. High cycle fatigue tests at a stress ratio of 0.8 were carried out on flat specimens from both steel conditions. Several characterization techniques, including optical microscopy, X-ray diffraction (XRD) and electron back scattered diffraction (EBSD), were used to detect and quantify the martensite induced by the cyclic deformation.