Non-intrusive efficiency estimation of inverter-fed induction machines

Motorised loads using induction machines use approximately 60% of the electricity globally. Most of these systems use three-phase induction motors due to their robustness and lower cost. They are often installed in continuously operating industrial plants/applications that require no operational interruptions. Whilst most of these induction machines are supplied from ideally sinusoidal supplies, applications are emerging where induction machines are fed from non-sinusoidal supplies. In particular, pulse width modulated inverters realize efficient control of induction machines in many automated industrial applications. From an energy management perspective, it is vital to continually assess the efficiency of induction machines in order to initiate replacement or economic repair. It is therefore of paramount importance that reliable and non-intrusive techniques for efficiency estimation of induction machines be investigated, that consider sinusoidal and non-sinusoidal supplies. This work proposes a non-intrusive efficiency estimation technique for inverter–fed induction motors that is based on harmonic regression analysis, harmonic equivalent circuit parameter estimation and harmonic loss analysis using limited measured data. Firstly, considerations for inverter-fed induction motor equivalent circuit modelling and parameter estimation techniques suitable for non-intrusive efficiency estimation are presented and the selection of one equivalent circuit for analysis is justified. Measured data is obtained from two different induction motors on a flexible 110kW test rig that utilises an HBM Gen 7i data acquisition system. By measuring voltage, current and input power at the supply terminals of the inverter-fed motor, the fundamental equivalent circuit parameters are estimated using population based incremental learning algorithm and compared with those obtained from the IEC 60034-2-1 Standard. The harmonic parameters are estimated using the bacterial foraging algorithm basing on the input impedance of the motor at each harmonic order. A finite harmonic loss analysis is carried out on the tested induction motors. The proposed techniques and harmonic loss analysis provide accurate efficiency estimates of within 1.5% error when compared to the direct method. Lastly, a related non-intrusive efficiency estimation technique is proposed that caters for a holistic loss contribution by all harmonics. The efficiency results from the proposed techniques are compared to those obtained from the IEC-TS 60034-2-3 Technical Specification and a direct method. The estimated efficiencies are comparable to those measured by the Technical Specification and a direct method within 2% error when tested on 37kW and 45kW PWM inverter-fed motors across the loading range. Furthermore, this work conducts a comprehensive non-intrusive rotor speed estimation comparative analysis in order to recommend the best technique(s), in terms of intrusiveness, accuracy and computational overhead. Errors of less than 1% have been reported in literature and experimental verification when using vibration analysis, Motor Current Signature Analysis (MCSA), Rotor Slot Harmonic (RSH) and Rotor Eccentricity Harmonic (REH) analysis techniques in inverter-fed IMs

Development of new methods for nonintrusive induction motor energy efficiency estimation

Induction motors (IMs) are the most widely used motors in industries. They constitute about 70% of the total motors used in industries and are the largest energy consumers in industrial applications. As a result of the increasing need for energy savings and demand-side management, the development of methods for accurate energy efficiency estimation has become a crucial area of research. While several methods have been proposed for induction motor efficiency determination, majority of the methods cannot be easily applied in the field owing to the intrusive nature of the test procedures involved. This PhD work presents some novel methods for nonintrusive efficiency estimation of induction motors operating on-site using limited motor terminal measurements and nameplate data. The first method is developed for induction motors operating on sinusoidal supply source (line-fed). The method uses a modified inverse Г-model equivalent circuit with series core loss arrangement to mitigate the inherent problems of higher computational burden and parameter redundancy associated with the conventional equivalent circuit method. Furthermore, a new method is presented for estimating the friction and windage loss using the airgap torque and motor nameplate data. The proposed Nonintrusive Field Efficiency Estimation (NFEE) technique was validated experimentally on four different induction motors for both balanced and unbalanced voltage supply conditions. The results demonstrate the accuracy of the proposed NFEE method and confirm its advantage over the conventional equivalent circuit method. In addition to the problem of unbalanced voltage supply, the presence of harmonics significantly affects the operation of induction motors. The second novel approach for estimating efficiency proposed in this PhD work extends the NFEE method to cover for non-sinusoidal supply condition. The method considers the variation of core loss, rotor bar resistance and leakage inductance due to time harmonics and skin effects. Finally, the efficiency estimations are compared to the IEC/TS 60034-2-3 in the case of a balanced non-sinusoidal supply condition. This allows not only the efficiency comparison but also the loss segregation analysis on the various components of the motor losses. In the case of an unbalanced supply, the efficiency results are compared to measured values obtained based on the direct input-output method. In both the first and second methods, a robust Chicken Swarm Optimization (CSO) algorithm has been used for the first time in conjunction with a simplified inverse Г-model EC to correctly determine the induction motor parameters and hence its losses and efficiency while inservice. As Variable Frequency Drives (VFDs) continue to dominate industrial process control, there is a need for stakeholders to quantify the converter-fed motor losses over a wide range of operating frequency and loading conditions. Although there is an increase in legislative activities, particularly in Europe, towards the classification and improvement of energy efficiency in electric drive systems, the handful of available standards for quantifying the harmonic losses are still undergoing validation. One of such standards is the IEC/TS 60034-2-3, which has been lauded as a step in the right direction. However, its limitation to rated motor frequency has been identified as one of its main weaknesses. Therefore, the third method proposed in this research demonstrates how the IEC/TS 60034-2-3 loss segregation methodology at nominal frequency can be extended over the constant-torque region of an induction motor (IM). The methodology has been validated by testing two motors using a 2-level voltage source inverter (VSI) in an open-loop V/F control mode. The results provide good feedback to the relevant IEC standards committee as well as guidance to stakeholders

A Precise, General, Non-Invasive and Automatic Speed Estimation Method for MCSA Diagnosis and Efficiency Estimation of Induction Motors

[EN] Efficiency estimation and diagnosis via MCSA require precise knowledge of speed. In an industrial environment, speed must be obtained with a non-invasive, automatic and general method. Recent studies have shown that Sensorless Speed Estimation techniques based on detecting Rotational Frequency Sideband Harmonics (RFSHs) or Rotor Slot Harmonics (RSHs) are best suited to these purposes. RFSHs-based methods are easier to apply as they only depend on the number of poles. RSHs-based are much more accurate due to their wider bandwidth. Yet, their use is not trivial as they require to identify the RSHs family, assign to each RSH its order of the current harmonic (¿) and determine the number of rotor slots (R), a rarely known parameter. This paper ends with this trade-off between accuracy and applicability by proposing a novel RSHs-based technique that, for the first time in technical literature, eliminates the need to estimate the number of rotor slots and provides a reliable and automatic procedure to locate the RSHs family and determine their ¿ indices. Finally, the method is validated under all types of conditions and motor designs, by simulations, lab tests and with 105 industrial motors, highlighting its high accuracy (errors below 0.05 rpm), and applicability.This work was supported by the Universitat Politecnica de Valencia and the Spanish Ministry of Science, Innovation and Universities [FPU19/02698]Bonet-Jara, J.; Pons Llinares, J. (2023). A Precise, General, Non-Invasive and Automatic Speed Estimation Method for MCSA Diagnosis and Efficiency Estimation of Induction Motors. IEEE Transactions on Energy Conversion. 38(2):1257-1267. https://doi.org/10.1109/TEC.2022.32208531257126738

A parameter estimation algorithm for induction machines using Artificial Bee Colony (ABC) optimization

Conventionally, parameters of the Induction Motor (IM) are determined using the standard noload and locked rotor test. Performing the no-load test is simple and involved running the machine uncoupled to a load, while measuring the power, voltage, current and shaft speed at different voltage test points. On the other hand, the locked rotor test requires full control of the rotor mechanically in the locked condition before measurements are taken. This paper presents a method for estimating the parameters of IMs without the need for the no-load and locked rotortests. The method is based on optimization approach using a relatively new swarm based algorithm called the Artificial Bee Colony (ABC) optimization. Two different equivalent circuits are implemented for the parameter estimation scheme; one with parallel and the other with series magnetization circuit. Parameters of a standard 7.5kW IM are estimated using the measured and estimated stator current, input and output power and the power factor. Based on the experimental results obtained, the optimization method using the ABC algorithm gave accurate estimates of the IM parameters when compared to the reference parameters determined using the IEEE standard 112-2004. The maximum errors of -13.730% and 2.249% are obtained for the parallel and series equivalent circuits respectively.Keywords: Inductions Machines, Parameter Estimation, Artificial Bee Colony, Magnetization Circuit, Optimization Algorith

Estimating induction motor efficiency under no-controlled conditions in the presences of unbalanced and harmonics voltages

This paper presents the application of a method to determine the output power, losses, and efficiency of induction motors, working in no-controlled conditions, in the presences of unbalanced and harmonics voltages. The method uses the steady state equivalent circuits, with some considerations for the analysis of motor performance, fed with unbalanced and harmonic voltages. The parameters of circuits are determined with low invasiveness, by applying a Bacterial Foraging Algorithm as technique of evolutionary search. With this, the efficiency and other operational parameters can be estimated at any operating point. The method was tested in a 12.6 kW motor working in an industrial network, with harmonics and voltage unbalanced

In Situ parameter estimation of synchronous machines using genetic algorithm method

The paper presents an in situ parameter estimation method to determine the equivalent circuit parameters of the Synchronous Machines. The parameters of synchronous generator, both cylindrical rotor and salient pole rotor, are estimated based on the circuit model. Genetic algorithm based parameter estimation technique is adopted where only one set of in-situ measured load test data is used. Conventional methods viz., EMF, MMF, Potier triangle method uses rated voltage and rated current obtained from more than one operating condition to determine the parameters. However, Genetic Algorithm (GA) based method uses the working voltage and load current of a single operating point obtained from in-situ measured load test data to estimate the parameters. The test results of the GA based parameter estimation method are found to be closer to direct load test results and better than conventional methods

A precise, General, Non-Invasive and Automatic Speed Estimation Method for MCSA Steady-State Diagnosis and Efficiency Estimation of Induction Motors in the 4.0 Industry

Tesis por compendio[ES] Hay dos aspectos cruciales a la hora de operar motores de inducción en la industria: la estimación de su eficiencia (para minimizar el consumo de energía) y su diagnóstico (para evitar paradas intempestivas y reducir los costes de mantenimiento). Para estimar la eficiencia del motor es necesario medir tensiones y corrientes. Por ello, resulta conveniente y muy útil utilizar la misma corriente para diagnosticar también el motor (Motor Current Signature Analysis: MCSA). En este sentido, la técnica MCSA más adecuada es aquella basada en la localización de armónicos de fallo en el espectro de la corriente de línea del estator en régimen permanente, pues esta es la condición de funcionamiento de la mayoría de los motores de inducción de la industria. Por otro lado, dado que la frecuencia de estos armónicos depende de la velocidad, resulta imprescindible conocer esta magnitud con precisión, ya que esto permite localizar correctamente los armónicos de fallo, y, por tanto, reducir las posibilidades de falsos positivos/negativos. A su vez, una medida precisa de la velocidad también permite calcular con precisión la potencia mecánica, lo que se traduce en una estimación más exacta del rendimiento. Por último, para adaptarse a las necesidades de la Industria 4.0, en la que se monitoriza continuamente un gran número de motores, la velocidad también debe ser obtenida de manera no invasiva, automática y para cualquier motor de inducción. A este respecto, dado que la medición precisa de la velocidad a través de un encóder es invasiva y costosa, las técnicas de estimación de velocidad sin sensores (SSE en inglés) se convierten en la mejor opción. En la primera parte de esta tesis se realiza un análisis exhaustivo de las familias de técnicas SSE presentes en la literatura técnica. Como se demuestra en ella, aquellos métodos basados en armónicos de ranura (RSHs en inglés) y en armónicos laterales de frecuencia rotacional (RFSHs) son potencialmente los únicos que pueden satisfacer todos los requisitos mencionados anteriormente. Sin embargo, como también se demuestra en esta parte, y hasta esta tesis, siempre había existido un compromiso entre la precisión (característica de los RSHs) y la aplicabilidad general del método (característica de los RFSHs). En la segunda parte, y núcleo de esta tesis, se presenta una metodología que acaba con este compromiso, proporcionando así el primer método de estimación de velocidad preciso, general, no invasivo y automático para el diagnóstico en estado estacionario MCSA y la estimación de la eficiencia de motores de inducción que operan en un contexto de Industria 4.0. Esto se consigue desarrollando una novedosa técnica basada en RSHs que, por primera vez en la literatura técnica, elimina la necesidad de conocer/estimar el número de ranuras del rotor, lo que había impedido hasta la fecha que estos métodos fueran de aplicación general. Esta técnica proporciona además un procedimiento fiable y automático para localizar la familia de RSHs en el espectro de la corriente de línea de un motor de inducción. De igual forma y sin la ayuda de un experto, la técnica es capaz de determinar los parámetros necesarios para estimar la velocidad a partir de los RSHs, utilizando medidas tomadas en régimen estacionario. La metodología es validada utilizando motores con diferentes características y tipos de alimentaciones, empleando para ello simulaciones, pruebas de laboratorio y 105 motores industriales. Además, se muestra un caso de aplicación industrial en el que el algoritmo desarrollado se implementa en un sistema de monitorización continua mediante MCSA, lo que acaba conduciendo al descubrimiento de un nuevo fallo en motores sumergibles de pozo profundo: el desgaste de los anillos de cortocircuito. Por último, se presenta una segunda aplicación directa para este tipo de motores derivada del procedimiento de detección de RSHs: el uso de estos armónicos para diagnosticar, en fase temprana, cortocircuitos entre espiras.[CA] Hi ha dos aspectes crucials a l'hora d'operar motors d'inducció en la indústria: l'estimació de la seua eficiència (per a minimitzar el consum d'energia) i el seu diagnòstic (per a evitar parades intempestives i reduir els costos de manteniment). Per a estimar l'eficiència del motor és necessari mesurar tensions i corrents. Per això, resulta convenient i molt útil utilitzar el mateix corrent per a diagnosticar també el motor (Motor Current Signature Analysis: MCSA). En aquest sentit, la tècnica MCSA més adequada és aquella basada en la localització d'harmònics de fallada en l'espectre del corrent de línia de l'estator en règim permanent, ja que aquesta és la condició de funcionament de la majoria dels motors d'inducció de la indústria. D'altra banda, atés que la freqüència d'aquests harmònics depén de la velocitat, resulta imprescindible conéixer aquesta magnitud amb precisió, ja que això permet localitzar correctament els harmònics de fallada i, per tant, reduir les possibilitats de falsos positius/negatius. Al seu torn, una mesura precisa de la velocitat també permet calcular amb precisió la potència mecànica, la qual cosa es tradueix en una estimació més exacta del rendiment. Finalment, per a adaptar-se a les necessitats de la Indústria 4.0, en la qual es monitora contínuament un gran nombre de motors, la velocitat també ha de ser obtinguda de manera no invasiva, automàtica i per a qualsevol motor d'inducció. En aquest sentit, atès que el mesurament precís de la velocitat a través d'un encóder és invasiva i costosa, les tècniques d'estimació de velocitat sense sensors (SSE en anglés) es converteixen en la millor opció. En la primera part d'aquesta tesi es realitza una anàlisi exhaustiva de totes les famílies de tècniques SSE presents en la literatura tècnica. Com es demostra en ella, aquells mètodes basats en harmònics de ranura (RSHs en anglès) i harmònics laterals de freqüència rotacional (RFSHs en anglés) són els més prometedors, ja que son potencialment els únics que poden satisfer tots els requisits esmentats anteriorment. No obstant això, com també es demostra en aquesta part, i fins a aquesta tesi, sempre havia existit un compromís entre la precisió (característica dels RSHs) i l'aplicabilitat general del mètode (característica dels RFSHs). En la segona part, i nucli d'aquesta tesi, es presenta una metodologia que acaba amb aquest compromís, proporcionant així el primer mètode d'estimació de velocitat precís, general, no invasiu i automàtic per al diagnòstic en estat estacionari MCSA i l'estimació de l'eficiència de motors d'inducció que operen en un context d'Indústria 4.0. Això s'aconsegueix desenvolupant una nova tècnica basada en RSHs que, per primera vegada en la literatura tècnica, elimina la necessitat de conéixer/estimar el nombre de ranures del rotor, cosa que havia impedit fins avui que aquests mètodes foren d'aplicació general. Aquesta tècnica proporciona a més un procediment fiable i automàtic per a localitzar la família de RSHs en l'espectre del corrent de línia d'un motor d'inducció. De la mateixa forma i sense l'ajuda d'un expert, la tècnica és capaç de determinar els paràmetres necessaris per a estimar la velocitat a partir dels RSHs, utilitzant mesures preses en règim estacionari. La metodologia és validada utilitzant motors amb diferents característiques i condicions d'alimentació, emprant per a això simulacions, proves de laboratori i 105 motors industrials. A més, es mostra un cas real d'aplicació industrial en el qual l'algoritme desenvolupat és implementat en un sistema de monitoratge continu mitjançant MCSA, la qual cosa acaba conduint al descobriment d'una nova fallada en motors submergibles de pou profund: el desgast dels anells de curtcircuit. Finalment, es presenta una segona aplicació directa per a aquest tipus de motors derivada del procediment de detecció de RSHs: l'ús d'aquests harmònics per a diagnosticar, en fase primerenca, curtcircuits entre espires.[EN] There are two crucial aspects when operating induction motors in industry: efficiency estimation (to minimize energy consumption) and diagnosis (to avoid untimely outages and reduce maintenance costs). To estimate the motor's efficiency, it is necessary to measure voltages and currents. Hence, it is convenient and very useful using the same current to also diagnose the motor (Motor Current Signature Analysis: MCSA). In this regard, the most suitable MCSA technique is that based on locating fault harmonics in the spectrum of the stator line current under steady-state, as this is the operating condition of most induction motors in industry. Since the frequency of these harmonics depends on the speed, it becomes essential to be able to know this magnitude with precision, as this makes it possible to correctly locate the fault harmonics, and therefore, reduce the chances of false positives/negatives. In turn, an accurate speed information also allows to calculate the mechanical power with precision, which results in a more accurate estimation of the motor performance. Finally, to adapt to the needs of 4.0 Industry, where large numbers of motors are continuously monitored, the speed must not only be obtained very accurately, but also non-invasively, automatically (without the need for an expert) and for any induction motor. In this regard, since precise speed measurement through a shaft sensor is invasive and expensive, Sensorless Speed Estimation (SSE) techniques become the best option. The first part of this thesis conducts a thorough analysis of all the families of SSE techniques present in the technical literature. As demonstrated therein, those techniques based on Slotting and Rotational Frequency Sideband Harmonics are the most promising, as they can potentially meet all the aforementioned requirements. However, as also proved in this part, and up to this thesis, there had always been a trade-off between accuracy, characteristic of Rotor Slot Harmonics (RSHs), and general applicability, characteristic of Rotational Frequency Sideband Harmonics (RFSHs). The second part, and core of this thesis, presents a methodology that ends with this trade-off between accuracy and general applicability, thus providing the first precise, general, noninvasive and automatic speed estimation method for MCSA steady-state diagnosis and efficiency estimation of induction motors that operate in a 4.0 Industry context. This is achieved by developing a novel RSH-based technique that, for the first time in technical literature, eliminates the need to know/estimate the number of rotor slots, which had so far prevented these techniques to be generally applicable. This technique also provides a reliable and automatic procedure to, from among the high number of significant harmonics present in the spectrum of the line current of an induction motor, locate the RSHs family. Also automatically and without the help of an expert, the technique is able to determine the parameters needed to estimate speed from RSHs, using only measurements taken during the motor normal operation at steady-state. The methodology is validated using motors with different characteristics and supply conditions, by simulations, lab tests and with 105 industrial motors. Furthermore, a real industrial case of application is shown as well, where the speed estimation algorithm is implemented in a continuous motor condition monitoring system via MCSA, which eventually leads to the discovery of a new fault in deep-well submersible motors: the wear of end-rings. Finally, a second direct application derived from the reliable and automatic procedure to detect RSHs is presented: the use of these harmonics to diagnose early-stage inter-turn faults in induction motors of deep-well submersible pumps.Bonet Jara, J. (2023). A precise, General, Non-Invasive and Automatic Speed Estimation Method for MCSA Steady-State Diagnosis and Efficiency Estimation of Induction Motors in the 4.0 Industry [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/194269Compendi

Algorithms for In-situ Efficiency Determination of Induction Machines

Robust structure, high reliability and low maintenance costs allow induction motors to be widely-used in various industrial applications. In recent decades, due to the increased concerns on global warming, and the effort to enhance the efficiency of tools, equipment, and systems, efficiency of induction machines (IMs) has received a lot of attention. The rated efficiency of an IM can be found on the nameplate. However, it is affected by aging, ambient temperature, load, supplied voltage and other technical reasons. Furthermore, based on NEMA MG 1 standard, the actual efficiency of an IM may vary from the nameplate value. As a result, efficiency estimation of IMs is essential to evaluate the efficiency of the whole system and energy cost. Applying available international standards to in-situ machines needs load decoupling and in some cases, the no-load/locked-rotor test is required. This is not allowed with in-situ machines. Therefore, having a non-intrusive method which is capable of estimating the efficiency of the machine by using only available data such as the input voltages, currents, active power and nameplate data is necessary. This thesis investigates in-situ methods to determine the efficiency of IMs and three related subjects are addressed. First, an optimization based algorithm is proposed to determine the efficiency of the IM at different loads. This algorithm is proven to have minimum intrusiveness and only uses the data of one operating point of the machine. Assumptions and techniques to increase the accuracy of the algorithm are addressed. The proposed algorithm is then applied to two conditions. In the first condition, the required input data are recorded when the machine reaches its thermal stability and final temperature rise of the machine is used as an input. In the second condition, the required input data are recorded 30 minutes after start of the machine and then the machine final temperature rise is predicted. Two approaches are proposed to predict final temperature rise and are based on machine insulation class and temperature rise of the machine in the first 30 minutes of operation of the machine after start. Moreover, a method is proposed to determine the range of IM equivalent circuit parameters and improve the probability of converging to the correct answer. The method is based on the nameplate data of the machine and empirical results provided by Hydro-Québec. The method is also improved by using the operating data of the machine. The proposed range determination is very helpful for in-situ applications where the output power of the machine is not available. Second, two dimensional finite element analysis (FEA) is used to predict the efficiency of the IMs at different loads. Two methodologies are adopted. In the first methodology, the losses are calculated directly using FEA while in the second one, the equivalent circuit parameters are first estimated using FEA and then the efficiency at different loads are estimated using the equivalent circuit parameters. To improve the results, a simple formula based on the rated power of the machine is proposed to evaluate the friction and windage losses also known as the mechanical loss of the machine. The proposed formula is applicable for 4-pole 60 Hz IMs and was achieved after study of more than 100 IMs of this type. Third, the effects of the adjustable-speed drives on the losses and efficiency of the IMs are addressed. The direct torque control and scalar control schemes implemented by an industrial drive are employed to control two types of IMs. Two IMs designed for direct-fed application and two other IMs designed for PWM applications are studied while method B of IEEE Std-112 is applied to segregate the losses. Variations of different losses at drive-fed and direct-fed conditions are compared and results are discussed

Power quality and electromagnetic compatibility: special report, session 2

The scope of Session 2 (S2) has been defined as follows by the Session Advisory Group and the Technical Committee: Power Quality (PQ), with the more general concept of electromagnetic compatibility (EMC) and with some related safety problems in electricity distribution systems. Special focus is put on voltage continuity (supply reliability, problem of outages) and voltage quality (voltage level, flicker, unbalance, harmonics). This session will also look at electromagnetic compatibility (mains frequency to 150 kHz), electromagnetic interferences and electric and magnetic fields issues. Also addressed in this session are electrical safety and immunity concerns (lightning issues, step, touch and transferred voltages). The aim of this special report is to present a synthesis of the present concerns in PQ&EMC, based on all selected papers of session 2 and related papers from other sessions, (152 papers in total). The report is divided in the following 4 blocks: Block 1: Electric and Magnetic Fields, EMC, Earthing systems Block 2: Harmonics Block 3: Voltage Variation Block 4: Power Quality Monitoring Two Round Tables will be organised: - Power quality and EMC in the Future Grid (CIGRE/CIRED WG C4.24, RT 13) - Reliability Benchmarking - why we should do it? What should be done in future? (RT 15