Computationally Efficient Optimization of a Five-Phase Flux-Switching PM Machine Under Different Operating Conditions

This paper investigates the comparative design optimizations of a five-phase outer-rotor flux-switching permanent magnet (FSPM) machine for in-wheel traction applications. To improve the comprehensive performance of the motor, two kinds of large-scale design optimizations under different operating conditions are performed and compared, including the traditional optimization performed at the rated operating point and the optimization targeting the whole driving cycles. Three driving cycles are taken into account, namely, the urban dynamometer driving schedule (UDDS), the highway fuel economy driving schedule (HWFET), and the combined UDDS/HWFET, representing the city, highway, and combined city/highway driving, respectively. Meanwhile, the computationally efficient finite-element analysis (CE-FEA) method, the cyclic representative operating points extraction technique, as well as the response surface methodology (in order to minimize the number of experiments when establishing the inverse machine model), are presented to reduce the computational effort and cost. From the results and discussion, it will be found that the optimization results against different operating conditions exhibit distinct characteristics in terms of geometry, efficiency, and energy loss distributions. For the traditional optimization performed at the rated operating point, the optimal design tends to reduce copper losses but suffer from high core losses; for UDDS, the optimal design tends to minimize both copper losses and PM eddy-current losses in the low-speed region; for HWFET, the optimal design tends to minimize core losses in the high-speed region; for the combined UDDS/HWFET, the optimal design tends to balance/compromise the loss components in both the low-speed and high-speed regions. Furthermore, the advantages of the adopted optimization methodologies versus the traditional procedure are highlighted

Hierarchical modeling for an industrial implementation of a Digital Twin for electrical drives

Digital twins have become popular for their ability to monitor and optimize a process or a machine, ideally through its complete life cycle using simulations and sensor data. In this paper, we focus on the challenge of accurate and real-time simulations for digital twins in the context of electrical machines. To build such a digital twin involves not only computational models for the electromagnetic aspects, but also mechanical and thermal effects need to be taken into account. We address mathematical tools that can be employed to carry out the required simulations based on physical laws as well as surrogate or data-driven models. One of those tools is a model hierarchy of very fine to very coarse models as well as reduced order models for obtaining real-time simulations. The required software tools to carry out simulations in the digital twin are also discussed. The simulation models are implemented in a pipeline that allows for the automatic modeling of new machines and the automatic configuration of new digital twins. Finally, the overall implemented digital twin is tested and implemented in a physical demonstrator

Thermal Management of E–Motors in Electric Vehicle Application Employing LPTN Model

The electric motor is at the center focus as an alternative to the internal combustion engine for automotive applications since it does not produce greenhouse gas emissions and can contribute significantly to the reduction of fossil fuel consumption globally. As extensive research works are being done on electric vehicles at present, thermal analysis of traction motor is increasingly becoming the key design factor to produce electric motors with high power and torque capabilities in order to satisfy electric vehicle driving requirements. Motor losses cause active heat generation in the motor components and excessive temperature rise affects the electromagnetic performance of the traction motor. High torque and power requirements based on the driving conditions under urban and highway drive conditions demand high capacity motor cooling system in order to keep the temperature within the safe limit. Hence, it is critical to develop and design a temperature prediction tool to dynamically estimate the winding and magnet temperature and regulate cooling to remove excessive heat from the motor. Conventional thermal modeling of motors includes analytical and numerical modeling. Analytical modeling is done by using Lumped Parameter Thermal Network (LPTN) which is analogous to electric circuit and a fast method for predicting temperature. It uses heat transfer equations involving thermal resistances and thermal capacitances to analytically determine temperature at different nodes. Numerical modeling is done in two ways–Finite Element Analysis and Computational Fluid Dynamics. Numerical modeling can produce more accurate results, but it requires more computational time. Since the temperature of motor components has to be predicted very quickly, i.e. during driving, LPTN is more effective because LPTN can quickly predict temperature based on the heat transfer equations. This thesis proposes an LPTN model that predicts motor temperature and regulates the required coolant flow rate simultaneously. Thus, it is able to dynamically predict the temperature. MATLAB Simulink has been used for simulation of the LPTN model for a laboratory PMSM prototype. The thermal resistances in the thermal network model have been obtained from the motor geometrical parameters. The electromagnetic loss data with respect to torque and speed were taken as input, and thus the temperature results of motor components have been found. The future work will be to implement this model into full scale prototype of the motor

Design and Application of Electrical Machines

Electrical machines are one of the most important components of the industrial world. They are at the heart of the new industrial revolution, brought forth by the development of electromobility and renewable energy systems. Electric motors must meet the most stringent requirements of reliability, availability, and high efficiency in order, among other things, to match the useful lifetime of power electronics in complex system applications and compete in the market under ever-increasing pressure to deliver the highest performance criteria. Today, thanks to the application of highly efficient numerical algorithms running on high-performance computers, it is possible to design electric machines and very complex drive systems faster and at a lower cost. At the same time, progress in the field of material science and technology enables the development of increasingly complex motor designs and topologies. The purpose of this Special Issue is to contribute to this development of electric machines. The publication of this collection of scientific articles, dedicated to the topic of electric machine design and application, contributes to the dissemination of the above information among professionals dealing with electrical machines

A high-speed permanent-magnet machine for fault-tolerant drivetrains

This paper details the design considerations of a permanent magnet (PM), three phase, high speed, synchronous machine for fault tolerant operation. A multidisciplinary approach to the optimal design of the machine is adopted targeted at minimising the additional losses resulting from faulty operating conditions and accounting for the remedial control strategy implemented. The design of a closed slot, 6 slots, 4 pole machine is presented. The machine is prototyped and tested to validate the analytical-computational performances predicted in the design and analysis stage under healthy and faulty condition

Performance of Induction Machines

Induction machines are one of the most important technical applications for both the industrial world and private use. Since their invention (achievements of Galileo Ferraris, Nikola Tesla, and Michal Doliwo-Dobrowolski), they have been widely used in different electrical drives and as generators, thanks to their features such as reliability, durability, low price, high efficiency, and resistance to failure. The methods for designing and using induction machines are similar to the methods used in other electric machines but have their own specificity. Many issues discussed here are based on the fundamental achievements of authors such as Nasar, Boldea, Yamamura, Tegopoulos, and Kriezis, who laid the foundations for the development of induction machines, which are still relevant today. The control algorithms are based on the achievements of Blaschke (field vector-oriented control) and Depenbrock or Takahashi (direct torque control), who created standards for the control of induction machines. Today’s induction machines must meet very stringent requirements of reliability, high efficiency, and performance. Thanks to the application of highly efficient numerical algorithms, it is possible to design induction machines faster and at a lower cost. At the same time, progress in materials science and technology enables the development of new machine topologies. The main objective of this book is to contribute to the development of induction machines in all areas of their applications

Performance analysis for a shaded-pole linear induction motor

Bibliography: pages 129-148.The induction motor remains the prime mover of present day industry with it's associated components in drive applications. In many such applications, fractional horse-power motors find ready use in small mechanisms where three-phase power supply is not available. In Southern Africa, these motors can be used is rural areas with simple reticulation systems, hence the renewed interest in the development of these low-power electrical motors, especially specialised models such as linear versions of such motors for special applications. This research is in the area of single-phase LIMs. The objective has been to model the shaded-pole LIM, in an attempt to enhance it's performance through improved design methods. This was carried out using an integrated analysis approach, involving circuital and field theory in the analysis of the practical motor, and computer simulation of it's equivalent model using the finite element method. Linear counterparts are possible for all the various forms of rotating electrical machines. All cylindrical machines can be 'cut' along a radial plane and 'unrolled' [32]. LIMs convert electrical energy directly into mechanical energy of translatory motion. Some advantages of linear version of induction motors are: they are gearless and often require minimal material thus minimising cost. While their scope of application are somewhat limited when compared to rotary versions, they do however give excellent performance in special situations where translator motion is required. However, the output power-to-mass and output power-to-volume of active materials ratio is reduced compared to rotary induction motors[45]. These disadvantages are caused by the large air-gap and the open magnetic circuit, which produces parasitical effects

Improved efficiency with adaptive front and rear axle independently driven powertrain and disconnect functionality

Front and rear axle independently driven (FRID) powertrains are becoming a popular solution for electric vehicles (EVs) due to torque distribution capability which can enhance powertrain energy efficiency. Typically, permanent magnet synchronous machines (PMSMs) are used for FRID powertrains due to their high torque, and power density. However, the drive-cycle efficiency of FRID powertrains with PMSMs is typically reduced in comparison to single motor drives. This is due to the unwanted no-load losses of PMSMs in the field weakening region. To overcome this drawback of PMSM FRIDs, this paper proposes an adaptive front- and rear-axle independently driven (AFRID) powertrain, utilizing two dog clutches, so that the powertrain can be operated in different modes (rear, front, and all-wheel drive) by adaptively connecting and disconnecting the front and/or rear electric drive unit (EDU). A rule-based mode selection strategy is developed to utilize the flexibility of different powertrain operating modes of the powertrain for maximizing the energy efficiency of the EDU. The simulation results show that the suggested AFRID powertrain, in comparison to a common FRID powertrain, can improve the WLTC drive-cycle consumption from 22.17 kWhh to 20.50 kWhh per 100 km. Based on the route and road-load information, the energy-saving potential of the AFRID powertrain can be further improved to 20.37 kWhh per 100 km by a suggested predictive mode selection strategy, achieving an optimal mode selection