Unequal Teeth Widths for Torque Ripple Reduction in Permanent Magnet Synchronous Machines With Fractional-Slot Non-Overlapping Windings

Permanent magnet synchronous machines with fractional-slot non-overlapping windings (FSPMSM), also known as tooth-coil winding permanent magnet synchronous machines (TCW PMSM), have been under intensive research during the latest decade. There are many optimization routines explained and implemented in the literature in order to improve the characteristics of this machine type. This paper introduces a new technique for torque ripple minimization in TCW PMSM. The source of torque harmonics is also described. The low order torque harmonics can be harmful for a variety of applications, such as direct drive wind generators, direct drive light vehicle electrical motors, and for some high precision servo applications. The reduction of the torque ripple harmonics with the lowest orders (6th and 12th) is realized by machine geometry optimization technique using finite element analysis (FEA). The presented optimization technique includes the stator geometry adjustment in TCW PMSMs with rotor surface permanent magnets and with rotor embedded permanent magnets. Influence of the permanent magnet skewing on the torque ripple reduction and cogging torque elimination was also investigated. It was implemented separately and together with the stator optimization technique. As a result, the reduction of some torque ripple harmonics was attained.

Analytic evaluation of three-phase short circuit demagnetization and hysteresis loss risk in rotor-surface-magnet Permanent-Magnet Synchronous Machines

Permanent magnet synchronous machines (PMSM) have become widely used in applications because of high efficiency compared to synchronous machines with exciting winding or to induction motors. This feature of PMSM is achieved through the using the permanent magnets (PM) as the main excitation source. The magnetic properties of the PM have significant influence on all the PMSM characteristics. Recent observations of the PM material properties when used in rotating machines revealed that in all PMSMs the magnets do not necessarily operate in the second quadrant of the demagnetization curve which makes the magnets prone to hysteresis losses. Moreover, still no good analytical approach has not been derived for the magnetic flux density distribution along the PM during the different short circuits faults. The main task of this thesis is to derive simple analytical tool which can predict magnetic flux density distribution along the rotor-surface mounted PM in two cases: during normal operating mode and in the worst moment of time from the PM’s point of view of the three phase symmetrical short circuit. The surface mounted PMSMs were selected because of their prevalence and relatively simple construction. The proposed model is based on the combination of two theories: the theory of the magnetic circuit and space vector theory. The comparison of the results in case of the normal operating mode obtained from finite element software with the results calculated with the proposed model shows good accuracy of model in the parts of the PM which are most of all prone to hysteresis losses. The comparison of the results for three phase symmetrical short circuit revealed significant inaccuracy of the proposed model compared with results from finite element software. The analysis of the inaccuracy reasons was provided. The impact on the model of the Carter factor theory and assumption that air have permeability of the PM were analyzed. The propositions for the further model development are presented.

Cost Reduction of Permanent Magnet Synchronous Machines

Electrical machine drives are the most electrical energy-consuming systems worldwide. The largest proportion of drives is found in industrial applications. There are, however many other applications that are also based on the use of electrical machines, because they have a relatively high efficiency, a low noise level, and do not produce local pollution. Electrical machines can be classified into several categories. One of the most commonly used electrical machine types (especially in the industry) is induction motors, also known as asynchronous machines. They have a mature production process and a robust rotor construction. However, in the world pursuing higher energy efficiency with reasonable investments not every application receives the advantage of using this type of motor drives. The main drawback of induction motors is the fact that they need slipcaused and thus loss-generating current in the rotor, and additional stator current for magnetic field production along with the torque-producing current. This can reduce the electric motor drive efficiency, especially in low-speed, low-power applications. Often, when high torque density is required together with low losses, it is desirable to apply permanent magnet technology, because in this case there is no need to use current to produce the basic excitation of the machine. This promotes the effectiveness of copper use in the stator, and further, there is no rotor current in these machines. Again, if permanent magnets with a high remanent flux density are used, the air gap flux density can be higher than in conventional induction motors. These advantages have raised the popularity of PMSMs in some challenging applications, such as hybrid electric vehicles (HEV), wind turbines, and home appliances. Usually, a correctly designed PMSM has a higher efficiency and consequently lower losses than its induction machine counterparts. Therefore, the use of these electrical machines reduces the energy consumption of the whole system to some extent, which can provide good motivation to apply permanent magnet technology to electrical machines. However, the cost of high performance rare earth permanent magnets in these machines may not be affordable in many industrial applications, because the tight competition between the manufacturers dictates the rules of low-cost and highly robust solutions, where asynchronous machines seem to be more feasible at the moment. Two main electromagnetic components of an electrical machine are the stator and the rotor. In the case of a conventional radial flux PMSM, the stator contains magnetic circuit lamination and stator winding, and the rotor consists of rotor steel (laminated or solid) and permanent magnets. The lamination itself does not significantly influence the total cost of the machine, even though it can considerably increase the construction complexity, as it requires a special assembly arrangement. However, thin metal sheet processing methods are very effective and economically feasible. Therefore, the cost of the machine is mainly affected by the stator winding and the permanent magnets. The work proposed in this doctoral dissertation comprises a description and analysis of two approaches of PMSM cost reduction: one on the rotor side and the other on the stator side. The first approach on the rotor side includes the use of low-cost and abundant ferrite magnets together with a tooth-coil winding topology and an outer rotor construction. The second approach on the stator side exploits the use of a modular stator structure instead of a monolithic one. PMSMs with the proposed structures were thoroughly analysed by finite element method based tools (FEM). It was found out that by implementing the described principles, some favourable characteristics of the machine (mainly concerning the machine size) will inevitable be compromised. However, the main target of the proposed approaches is not to compete with conventional rare earth PMSMs, but to reduce the price at which they can be implemented in industrial applications, keeping their dimensions at the same level or lower than those of a typical electrical machine used in the industry at the moment. The measurement results of the prototypes show that the main performance characteristics of these machines are at an acceptable level. It is shown that with certain specific actions it is possible to achieve a desirable efficiency level of the machine with the proposed cost reduction methods.

Influence of Travelling Current Linkage Harmonics on Inductance Variation, Torque Ripple and Sensorless Capability of Tooth-Coil Permanent-Magnet Synchronous Machines

This paper introduces an important source of torque ripple in PMSMs with tooth-coil windings (TC-PMSMs). It is theoretically proven that saturation and cross-saturation phenomena caused by the non-synchronous harmonics of the stator current linkage cause a synchronous inductance variation with a particular periodicity. This, in turn, determines the magnitude of the torque ripple and can also deteriorate the performance of signal-injection-based rotor position estimation algorithms. An improved dq- inductance model is proposed. It can be used in torque ripple reduction control schemes and can enhance the self-sensing capabilities of TC-PMSMs

Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis

Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.

Effect of adding unconventional raw materials on the technological properties of rice fresh pasta

The aim of this study was to develop fettuccini type rice fresh pasta by cold extrusion. To produce the pasta, a 2² Central Composite Rotational Design was used, in which the effects of the addition of pre-gelatinized rice flour - PGRF (0-60%) and modified egg albumin - MEA (0-10%) were studied. The dependent variables were the results of the cooking test and of the instrumental texture. The optimum cooking time for all of the formulations of rice fresh pasta was 3 minutes. MEA had a greater effect on increasing the weight of the pasta when compared to that of PGRF. It was found that with the addition of PGRF increase in loss of solids in cooking water, whereas MEA exerted the opposite effect on this parameter. Moreover, the maximum value of MEA (10%) had an optimum effect on pasta firmness, while PGRF had a negative effect on this parameter. The maximum values of PGRF and MEA reduced the stickiness of the pasta. Based on these results and on the parameters considered as most important, the rice pasta with the best technological characteristics was that with the maximum levels of MEA (10%) and no addition of PGRF (0%). This product was submitted to sensory and microbiological analyses, with good results.

Effect of adding flours from marolo fruit (Annona crassiflora Mart) and jerivá fruit (Syagrus romanzoffiana Cham Glassm) on the physicals and sensory characteristics of food bars

Abstract The marolo (Annona crassiflora Mart.) and jerivá (Syagrus romanzoffiana Cham Glassm) fruits grow in the Cerrado biome, and have important sensory and nutritional characteristics. These fruits are eaten fresh or processed and embedded in ice cream, candy, juices, and liquors. However, their use is very limited and is localized exclusively to their native region. The aim of this study was to evaluate the use of these fruits in food consumer products to improve the nutritional patterns of consumers and extend knowledge thereof. To do this, different levels (0%, 5%, 10%, 15%, and 20%) of flour derived from the marolo and jerivá fruits were incorporated into food bars, which were then characterized in terms of their physical of the texture (TPA), porosity, color and sensorial properties. The food bars enriched with marolo and jerivá flours had an intense yellow color and increased hardness relative to the control bars; the porosity of the bars progressively decreased as the amount of flour added increased. The sensorial analysis in the snack bars developed added with the fruits flour no was influence by incorporation this component, showed good averages for the scores evaluated.

Can future systemic financial risks be quantified?: ergodic vs nonergodic stochastic processes

Different axioms underlie efficient market theory and Keynes's liquidity preference theory. Efficient market theory assumes the ergodic axiom. Consequently, today's decision makers can calculate with actuarial precision the future value of all possible outcomes resulting from today's decisions. Since in an efficient market world decision makers "know" their intertemporal budget constraints, decision makers never default on a loan, i.e., systemic defaults, insolvencies, and bankruptcies are impossible. Keynes liquidity preference theory rejects the ergodic axiom. The future is ontologically uncertain. Accordingly systemic defaults and insolvencies can occur but can never be predicted in advance.

Parameter estimation for Chaotic or Stochastic Dynamics

Since its discovery, chaos has been a very interesting and challenging topic of research. Many great minds spent their entire lives trying to give some rules to it. Nowadays, thanks to the research of last century and the advent of computers, it is possible to predict chaotic phenomena of nature for a certain limited amount of time. The aim of this study is to present a recently discovered method for the parameter estimation of the chaotic dynamical system models via the correlation integral likelihood, and give some hints for a more optimized use of it, together with a possible application to the industry. The main part of our study concerned two chaotic attractors whose general behaviour is diff erent, in order to capture eventual di fferences in the results. In the various simulations that we performed, the initial conditions have been changed in a quite exhaustive way. The results obtained show that, under certain conditions, this method works very well in all the case. In particular, it came out that the most important aspect is to be very careful while creating the training set and the empirical likelihood, since a lack of information in this part of the procedure leads to low quality results.

Stochastic particle models: mean reversion and burgers dynamics. An application to commodity markets

The aim of this study is to propose a stochastic model for commodity markets linked with the Burgers equation from fluid dynamics. We construct a stochastic particles method for commodity markets, in which particles represent market participants. A discontinuity in the model is included through an interacting kernel equal to the Heaviside function and its link with the Burgers equation is given. The Burgers equation and the connection of this model with stochastic differential equations are also studied. Further, based on the law of large numbers, we prove the convergence, for large N, of a system of stochastic differential equations describing the evolution of the prices of N traders to a deterministic partial differential equation of Burgers type. Numerical experiments highlight the success of the new proposal in modeling some commodity markets, and this is confirmed by the ability of the model to reproduce price spikes when their effects occur in a sufficiently long period of time.

Finding Methods for Recognizing and Classifying Spare Part Criticality – Case Full Deposit Stripping Machines

The aim of this Master’s thesis is to find a method for classifying spare part criticality in the case company. Several approaches exist for criticality classification of spare parts. The practical problem in this thesis is the lack of a generic analysis method for classifying spare parts of proprietary equipment of the case company. In order to find a classification method, a literature review of various analysis methods is required. The requirements of the case company also have to be recognized. This is achieved by consulting professionals in the company. The literature review states that the analytic hierarchy process (AHP) combined with decision tree models is a common method for classifying spare parts in academic literature. Most of the literature discusses spare part criticality in stock holding perspective. This is relevant perspective also for a customer orientated original equipment manufacturer (OEM), as the case company. A decision tree model is developed for classifying spare parts. The decision tree classifies spare parts into five criticality classes according to five criteria. The criteria are: safety risk, availability risk, functional criticality, predictability of failure and probability of failure. The criticality classes describe the level of criticality from non-critical to highly critical. The method is verified for classifying spare parts of a full deposit stripping machine. The classification can be utilized as a generic model for recognizing critical spare parts of other similar equipment, according to which spare part recommendations can be created. Purchase price of an item and equipment criticality were found to have no effect on spare part criticality in this context. Decision tree is recognized as the most suitable method for classifying spare part criticality in the company.

Evaluation of the Efficiency of Line-Start Permanent-Magnet Machines as a Function of the Operating Temperature

The standard squirrel-cage induction machine has nearly reached its maximum efficiency. In order to further increase the energy efficiency of electrical machines, the use of permanent magnets in combination with the robust design and the line start capability of the induction machine is extensively investigated. Many experimental designs have been suggested in literature, but recently, these line-start permanent-magnet machines (LSPMMs) have become off-the-shelf products available in a power range up to 7.5 kW. The permanent magnet flux density is a function of the operating temperature. Consequently, the temperature will affect almost every electrical quantity of the machine, including current, torque, and efficiency. In this paper, the efficiency of an off-the-shelf 4-kW three-phase LSPMM is evaluated as a function of the temperature by both finite-element modeling and by practical measurements. In order to obtain stator, rotor, and permanent magnet temperatures, lumped thermal modeling is used.