Rotor-position detection in permanent-magnet wheel motor to ensure smooth startup from standstill

In this paper, an innovative rotor-position-detection method for a permanent-magnet wheel motor (PMWM) that operates from standstill to low speed is presented. The neutral voltage, which is sensed through phaseshifted pulse width modulation, overcomes the limitations of the conventional back electromotive force (EMF)-based position-detection method, which is more suitable for high-speed operation. In addition, a technique that ensures a transition between the two position-detection methods is presented to cover the full speed range. Computer simulations are employed to design and assess the neutral-voltage-based and EMF-based position-detection methods. The results of the position detection and angle error are presented starting from standstill to low speed. A step current (iq) corresponding to motor torque demand is applied for the starting process in the two position-detection methods. The experimental studies of the new position-detection method are conducted. The method is successfully applied to drive a 60-kW PMWM that operates from standstill to high speed. This demonstrates the effectiveness and performance of the presented method

Sliding mode control with observer for permanent magnet synchronous machine drives

This paper aims to develop the sliding mode control (SMC) scheme in sensorless permanent magnet synchronous machine (PMSM) drives to replace conventional proportional integral (PI) speed control. The SMC is formulated based on the integral sliding surface of the speed error. And the error is corrected based on the concept of Lyapunov stability. The SMC is designed with the load torque observer so that the disturbance can be estimated as feedback to the controller. The vector control technique which is also known as field-oriented control (FOC) is also used to split the stator current into the magnetic field generating part which is the direct axis and the torque generating part which is the quadrature axis. This can be done by using Park and Clarke transformations. The performance of the proposed SMC is tested under changes in load-torque and without load for different speed commands. The results prove that the SMC produces robust performances under variations of speeds and load disturbances. The effectiveness of the proposed method is verified and simulated by using MATLAB/SIMULINK software

Sensorless Control of Switched-Flux Permanent Magnet Machines

This thesis investigates the sensorless control strategies of permanent magnet synchronous machines (PMSMs), with particular reference to switched-flux permanent magnet (SFPM) machines, based on high-frequency signal injection methods for low speed and standstill and the back-EMF based methods for medium and high speeds

Artificial Intelligence Supported EV Electric Powertrain for Safety Improvement

As an environmentally friendly transport option, electric vehicles (EVs) are endowed with the characteristics of low fossil energy consumption and low pollutant emissions. In today's growing market share of EVs, the safety and reliability of the powertrain system will be directly related to the safety of human life. Reliability problems of EV powertrains may occur in any power electronic (PE) component and mechanical part, both sudden and cumulative. These faults in different locations and degrees will continuously threaten the life of drivers and pedestrians, bringing irreparable consequences. Therefore, monitoring and predicting the real-time health status of EV powertrain is a high-priority, arduous and challenging task. The purposes of this study are to develop AI-supported effective safety improvement techniques for EV powertrains. In the first place, a literature review is carried out to illustrate the up-to-date AI applications for solving condition monitoring and fault detection issues of EV powertrains, where recent case studies between conventional methods and AI-based methods in EV applications are compared and analysed. On this ground this study, then, focuses on the theories and techniques concerning this topic so as to tackle different challenges encountered in the actual applications. In detail, first, as for diagnosing the bearing system in the earlier fault period, a novel inferable deep distilled attention network is designed to detect multiple bearing faults. Second, a deep learning and simulation driven approach that combines the domain-adversarial neural network and the lumped-parameter thermal network (LPTN) is proposed for achieve IPMSM permanent magnet temperature estimation work. Finally, to ensure the use safety of the IGBT module, deep learning -based IGBT modules’ double pulse test (DPT) efficiency enhancement is proposed and achieved via multimodal fusion networks and graph convolution networks

Advances in the Field of Electrical Machines and Drives

Electrical machines and drives dominate our everyday lives. This is due to their numerous applications in industry, power production, home appliances, and transportation systems such as electric and hybrid electric vehicles, ships, and aircrafts. Their development follows rapid advances in science, engineering, and technology. Researchers around the world are extensively investigating electrical machines and drives because of their reliability, efficiency, performance, and fault-tolerant structure. In particular, there is a focus on the importance of utilizing these new trends in technology for energy saving and reducing greenhouse gas emissions. This Special Issue will provide the platform for researchers to present their recent work on advances in the field of electrical machines and drives, including special machines and their applications; new materials, including the insulation of electrical machines; new trends in diagnostics and condition monitoring; power electronics, control schemes, and algorithms for electrical drives; new topologies; and innovative applications

Proceedings of the 8th International Conference EEMODS'2013 Energy Efficiency in Motor Driven Systems

This book contains the papers presented at the eighth international conference on Energy Efficiency in Motor Driven Systems EEMODS 2013 EEMODS 2013 was organised in Rio de Janeiro, Brasil from 28 to 30 October 2013. This major international conference, which was previously been staged in Lisbon (1996), London (1999), Treviso (2002), Heidelberg (2005), Beijing (2007), Nantes (2009) and Washington DC (2011) has been very successful in attracting an international and distinguished audience, representing a wide variety of stakeholders in policy implementation and development, manufacturing and promotion of energy-efficient motor systems, including key policy makers, equipment manufacturers, academia and end-users. Potential readers who may benefit from this book include researchers, engineers, policymakers, energy agencies, electric utilities, and all those who can influence the design, selection, application, and operation of electrical motor driven systems.JRC.F.7-Renewables and Energy Efficienc

Contribución en el ámbito de la tecnología sensorless para la detección de la velocidad y posición en motores dc monitorizando únicamente la corriente: mejora de la precisión, minimización del coste computacional y aplicabilidad a motores de alta potencia

Actualmente en muchas aplicaciones es necesario conocer la velocidad y posición de un motor. Esto puede ser conseguido mediante observadores convencionales como son encoders, tacómetros o resolvers, o mediante observadores sensorless. Los observadores sensorless son técnicas que miden la tensión y/o la corriente y estiman la velocidad y posición. En motores DC, los observadores sensorless se dividen en tres grupos, los basados en el modelo dinámico, los basados en la componente ripple y los basados en la combinación del modelo dinámico y la componente ripple. Este trabajo presenta tres nuevos métodos donde cada uno de ellos presenta una mejora frente a los observadores sensorless existentes que monitorizan únicamente la corriente para la estimación de la velocidad y/o posición. El primer método funciona en motores dc de baja potencia, se basa en la componente ripple e intenta minimizar el efecto del ruido. El segundo método funciona en motores DC de baja potencia, se basa en la componen ripple e intenta minimizar el coste computacional. El tercer método funciona en motores DC de alta potencia, en este caso una nueva teoría sobre las componentes espectrales de la corriente ha sido desarrollada, y en esta teoría se basa para realizar la estimación. Finalmente los tres métodos han sido testeados y medida su precisión dando como resultado que tienen una precisión aceptable.Departamento de Teoría de la Señal y Comunicaciones e Ingeniería Telemátic

Proceedings of the 10th international conference on energy efficiency in motor driven systems (EEMODS' 2017)

The 10th International Conference on Energy Efficiency in Motor Driven Systems (EEMODS'17) was be held in Rome (Italy) on 6-8 September, 2017. The EEMODS conferences have been very successful in attracting distinguished and international presenters and attendees. The wide variety of stakeholders has included professionals involved in manufacturing, marketing, and promotion of energy efficient motors and motor driven systems and representatives from research labs, academia, and public policy. EEMODS’15 provided a forum to discuss and debate the latest developments in the impacts of electrical motor systems (advanced motors and drives, compressors, pumps, and fans) on energy and the environment, the policies and programmes adopted and planned, and the technical and commercial advances made in the dissemination and penetration of energy-efficient motor systems. In addition EEMODS covered also energy management in organizations, international harmonization of test method and financing of energy efficiency in motor systems. The Book of Proceedings contains the peer reviewed paper that have been presented at the conference.JRC.C.2-Energy Efficiency and Renewable