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Multivariable supervision systems for online monitoring of induction motors allow large versatility and diagnosis robustness. As regards rotor faults, the diagnostic procedure based on sideband current components may fail due to the presence of interbar currents that reduce the degree of rotor asymmetry and, thus, the amplitude of these spectral components. On the other hand, the interbar currents produce core vibrations in the axial direction; these vibrations can be detected using a suitable vibration sensor. In this paper, a differential fault analysis based on traditional motor current signature analysis (MCSA) and on radial and axial vibration monitoring is proposed to discern cases in which the presence of interbar currents decreases the sensitivity of MCSA. The features of stator currents and of radial and axial core vibration signals are investigated in order to increase the reliability of the diagnostic system. Moreover, to explore the possibility of obtaining further information, stray flux signals are taken into account. Index Terms--Condition monitoring, induction machines, motor current signature analysis (MCSA), stray flux, vibrations.

This paper describes a simple dc-dc step-up converter topology for switch-mode dc power supplies. The proposed configuration is well suited for high-power applications with battery supply. In the automotive framework, the push-pull architecture is the most widespread. However, as power increases, the use of a full-bridge architecture is mandatory. This paper presents a full-bridge architecture where the traditional single-phase transformer is replaced by a three-phase transformer. A prototype was realized and tested for the power supply of automotive devices. In this environment, one of the most important requirements is the ability to provide a burst of power during short-duration events, together with high-efficiency and high-quality output voltage. The latter constraints can be achieved by only using closed-loop switch-mode dc-dc converters at high switching frequency, thus reducing converter efficiency and creating electromagnetic-compatibility (EMC) problems. In this paper, the aforementioned issues were tackled relying on an open-loop topology. Open-loop converters are feasible if the output resistance of the converter is as low as possible, and a possible solution is the minimization of power losses. The solution is the use of a three-phase transformer with a delta-wye connection within a full-bridge converter topology. The configuration will be referred to as 3boost power supply. The three-phase transformer replaces the common single-phase transformer, and it is driven by a three-phase full-bridge inverter operating in six-step modulation. At secondary, a three-phase full wave diode rectifier is used to obtain the output dc voltage level. Therefore, a unitary transformer utilization factor is achieved. A simple theoretical comparison between the three types of converters--push-pull, conventional full bridge, and 3boost is shown. A low-power version of the converter was realized. Experiments confirm that this topology allows to achieve a high efficiency, a lower ripple factor, and a good EMC behavior. Index Terms--DC-DC power conversion, pulsewidth-modulated power converters.

This paper describes the realization of a high-performance drive based on stepping motors, with a specific reference to the optimal choice of pulsewidth modulation. An original modulation technique is proposed that allows, in conjunction with current feedback, to achieve high performances together with a reduced current ripple. A prototype digital signal processor-based drive was realized for a small-size stepping motor. Index Terms--Motor drives, pulsewidth modulation (PWM), stepper motors.

Several techniques were presented in the literature in order to perform accurate tracking of frequencies for different purposes. Most of them are modified versions of the traditional discrete Fourier transform (DFT) or other spectrum-estimation techniques. This paper presents a procedure based on the statistical analysis of the current signal in the time domain, referred to as maximum covariance method for frequency tracking (MCMFT), which allows to obtain high-frequency resolution independent of the sampling frequency and of the time acquisition period. Owing to the proposed procedure, the spectrum lines related to supply frequency or to rotor-slotting frequency for an induction machine can be detected with extreme accuracy within a wide range of sampled data conditions. Then, an accurate slip computation, or speed estimation, for sensorless control or distribution network diagnosis can be performed. Comparisons between previously existing methods and the proposed one are reported, in order to critically analyze its performances. Two different-sized induction machines were used for the experiments. Index Terms--Frequency estimation, power system monitoring, signal processing.

Different types of electric vehicles (EVs) have been recently designed with the aim of solving pollution problems caused by the emission of gasoline-powered engines. Environmental problems promote the adoption of new-generation electric vehicles for urban transportation. As it is well known, one of the weakest points of electric vehicles is the battery system. Vehicle autonomy and, therefore, accurate detection of battery state of charge (SoC) together with battery expected life, i.e., battery state of health, are among the major drawbacks that prevent the introduction of electric vehicles in the consumer market. The electric scooter may provide the most feasible opportunity among EVs. They may be a replacement product for the primary-use vehicle, especially in Europe and Asia, provided that drive performance, safety, and cost issues are similar to actual engine scooters. The battery system choice is a crucial item, and thanks to an increasing emphasis on vehicle range and performance, the Li-ion battery could become a viable candidate. This paper deals with the design of a battery pack based on Li-ion technology for a prototype electric scooter with high performance and autonomy. The adopted battery system is composed of a suitable number of cells series connected, featuring a high voltage level. Therefore, cell equalization and monitoring need to be provided. Due to manufacturing asymmetries, charge and discharge cycles lead to cell unbalancing, reducing battery capacity and, depending on cell type, causing safety troubles or strongly limiting the storage capacity of the full pack. No solution is available on the market at a cheap price, because of the required voltage level and performance, therefore, a dedicated battery management system was designed, that also includes a battery SoC monitoring. The proposed solution features a high capability of energy storing in braking conditions, charge equalization, overvoltage and undervoltage protection and, obviously, SoC information in order to optimize autonomy instead of performance or vice-versa. Index Terms--Batteries, electric vehicles (EVs).

The experience gained by ENEL Produzione (previously the Italian Electric Board) on monitoring large induction motors cage condition is reported in this paper. The diagnostic procedure is based on the motor current signature analysis and, in particular, on the two sideband current components near the frequency fundamental line that appear in the current power spectrum when a rotor bar/ring breakage occurs. According to the developed procedure, a diagnostic index obtained from these components is stored and its trend as a function of time allows for the detection of the occurrence of a failure in most cases. This event is clearly shown by the overcoming of a prefixed and triggered threshold. Moreover, machines with particular rotor magnetic structure are considered. In this case, unexpectedly high sideband components appear, even in the presence of healthy cages, and the test procedure was adapted to account for these conditions. Index Terms--Diagnostics, induction machines.

A fully digital control scheme is presented, based on a particular type of flux observer. This includes a quite accurate magnetic model of the motor, taking into account cross saturation. This model is first described and, then, the practically obtained control performance is shown, giving evidence to the impact of such a model on the system behavior. Index Terms - AC drives, digital control, observer-based control, synchronous reluctance drive.

A design approach oriented to minimization of torque ripple is presented for synchronous reluctance motors of the transverse-laminated type. First, the possible types of rotors are classified and the more suited rotor structure is evidenced, to be matched to a given stator. Then, the inner rotor design is described, pointing out the low-ripple measures. Last, experimental results are given from three different rotors; they confirm the validity of the proposed approach. Index Terms - Electrical machines, synchronous reluctance motor, torque ripple minimization.

Various applications of artificial intelligence (AI) techniques (expert systems, neural networks, and fuzzy logic) presented in the literature prove that such technologies are well suited to cope with on-line diagnostic tasks for induction machines. The features of these techniques and the improvements that they introduce in the diagnostic process are recalled, showing that, in order to obtain indication on the fault extent, faulty machine models are still essential. Moreover, by the models, that must trade off between simulation result effectiveness and simplicity, it is possible to overcome crucial points of the diagnosis. With reference to rotor electrical faults of induction machines, a new and simple procedure based on a model which includes the speed ripple effect is developed. This procedure leads to a new diagnostic index, independent of the machine operating condition and inertia value, that allows the implementation of the diagnostic system with a minimum configuration intelligence. Index Terms - Artificial intelligence, diagnostics, induction machines.

Based on a (d, q) synchronous frame, the control problems of synchronous reluctance motors are outlined. In particular, the effect of magnetic saturation, core loss, and angular measurement errors of various types are evidenced. A flux-observer-based control scheme, capable of overcoming most of the above problems, is proposed. The proposed control has been implemented on a prototype drive, adopting a 17-N-m 8000-r/min motor. The experimental results show quite a good performance, with particular emphasis on those applications which require a large constant-power speed range. Index Terms - Electrical drives, observer-based control, synchronous reluctance motor.

Three ac motors are compared for application in high-performance controlled drives: induction, brushless, and synchronous reluctance motors. Their design is optimized under common design assumptions. Then, the given stall-torques are compared to each other. In addition, the quadrature reactances are compared, as affecting overload and flux-weakening performances. Last, applicative considerations are given, thus defining the most suitable solution for each field.

An improvement of induction machine rotor fault diagnosis based on a neural network approach is presented. A neural network can substitute in a more effective way the faulted machine models used to formalize the knowledge base of the diagnostic system when inputs and outputs are suitably chosen. Training the neural network by data achieved through experimental tests on healthy machines and through simulation in case of faulted machines, the diagnostic system can discern between 'healthy' and 'faulty' machines. This procedure substitutes the statement of a trigger threshold, required by the diagnostic procedure based on the machine models.

The paper reports the comparison and performance evaluation of different diagnostic procedures that use input electric signals to detect and quantify rotor breakage in induction machines supplied by the mains. Besides the traditional current signature analysis based on one-phase current spectrum lines at frequencies (1 [+ or -] 2s)f, the procedures based on analysis of the line at frequency 2s f in the spectrum respectively of electromagnetic torque, space vector current modulus, and instantaneous power are considered. These last procedures have similar features and the comparison is developed on the basis of instantaneous torque. It is addressed that the speed ripple introduces two further terms in the instantaneous torque, decreasing the accuracy of the diagnosis. It is shown that there is a link between the angular displacement of the current sideband components at frequencies (1 [+ or -] 2s)f. This allows a more correct quantitative evaluation of the fault and shows the superiority of the sideband current components diagnostic procedure over the other proposed methods. Index Terms--Diagnostics, induction machines, rotor faults.

This paper presents a review of the most recent developments in the field of diagnosis of electrical machines and drives based on artificial intelligence (AI). It covers the application of expert systems, artificial neural networks (ANNs), and fuzzy logic systems that can be integrated into each other and also with more traditional techniques. The application of genetic algorithms is considered as well. In general, a diagnostic procedure starts from a fault tree developed on the basis of the physical behavior of the electrical system under consideration. In this phase, the knowledge of well-tested models able to simulate the electrical machine in different fault conditions is fundamental to obtain the patterns characterizing the faults. The fault tree navigation performed by an expert system inference engine leads to the choice of suitable diagnostic indexes, referred to a particular fault, and relevant to build an input data set for specific AI (NNs, fuzzy logic, or neuro-fuzzy) systems. The discussed methodologies, that play a general role in the diagnostic field, are applied to an induction machine, utilizing as input signals the instantaneous voltages and currents. In addition, the supply converter is also considered to incorporate in the diagnostic procedure the most typical failures of power electronic components. A brief description of the various AI techniques is also given; this highlights the advantages and the limitations of using AI techniques. Some applications examples are also discussed and areas for future research are also indicated. Index Terms--Artificial intelligence, drives diagnostics, electrical machines.

In this paper, the impact of control on faulted induction machine behavior is presented. The diagnostic indexes usually used for open-loop operation are no longer effective. Simulation and experimental results show that the spectrum of the field current component [i.sub.d] in a field-oriented controlled machine has suitable features that can lead to an effective diagnostic procedure. Specifically, in the case of stator and rotor faults the [i.sub.d] spectrum components at frequencies 2f and 2sf, respectively, are quite independent of control parameters and dependent on the fault extent. Index Terms--Fault diagnosis, induction motor drives.

The cross-saturation phenomenon in synchronous reluctance motors is extensively analyzed, with a main reference to motors of the transverse-laminated type. A mixed theoretical and experimental approach is adopted, aiming at definition of the motor's behavior when large overload currents are driven up to ten times the rated current. As a consequence, a special test and measuring procedure has been adopted. The obtained results are used to check the validity of the adopted model and to prove the unexpected overload performance of this motor. Index Terms--Magnetic cross saturation, synchronous reluctance machines.

This paper deals with the electric tracing of the load variation of an induction machine supplied by the mains. A load trouble, like a torque dip, affects the machine supply current and consequently it should be possible to use the current pattern to detect features of the torque pattern, using the machine itself as a torque sensor. But current signature depends on many phenomena and misunderstandings are possible. At first the effect of different load anomalies on current spectrum, in comparison with other machine troubles like rotor asymmetries, are investigated. Reference is made to low frequency torque disturbances, which cause a quasistationary machine behavior. Simplified relationships, validated by simulation results and by experimental results, are developed to address the current spectrum features. In order to detect on-lines anomalies, a current signature extraction is performed by the time-frequency spectrum approach. This method allows the detection of random fault as well. Finally it is shown that a Neural Network approach can help the torque pattern recognition, improving the interpretation of machine anomalies effects. Index Terms--Diagnostics, induction motor, load anomalies, monitoring, neural network.