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

Water-pumping permanent magnet synchronous motor optimization based on customized torque-speed operating area and performance characteristics

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis paper presents a novel methodology for optimizing Permanent Magnet Synchronous Motors for Water-Pumping applications. The algorithm is designed to start the optimization process from a predefined torque-speed area, its desired envelope, and the performance characteristics of the motor to be obtained after the optimization process, providing the information in an efficiency map, according to a predefined control strategy (MTPA, MTPV, etc.). This work also implements an image comparison technique based on the structural similarity index to evaluate the objective function.Peer ReviewedPostprint (author's final draft

Optimal design of a three-phase AFPM for in-wheel electrical traction

Sinusoidally fed permanent magnet synchronous motors (PMSM) fulfill the special features required for traction motors to be applied in electric vehicles (EV). Among them, axial flux permanent magnet (AFPM) synchronous motors are especially suited for in-wheel applications. Electric motors used in such applications must meet two main requirements, i.e. high power density and fault tolerance. This paper deals with the optimal design of an AFPM for in-wheel applications used to drive an electrical scooter. The single-objective optimization process carried out in this paper is based on designing the AFPM to obtain an optimized power density while ensuring appropriate fault tolerance requirements. For this purpose a set of analytical equations are applied to obtain the geometrical, electric and mechanical parameters of the optimized AFPM and several design restrictions are applied to ensure fault tolerance capability. The optimization process is based on a genetic algorithm and two more constrained nonlinear optimization algorithms in which the objective function is the power density. Comparisons with available data found in the technical bibliography show the appropriateness of the approach developed in this work.Postprint (published version

Comparison of Geometric Optimization Methods with Multiobjective Genetic Algorithms for Solving Integrated Optimal Design Problems

In this paper, system design methodologies for optimizing heterogenous power devices in electrical engineering are investigated. The concept of Integrated Optimal Design (IOD) is presented and a simplified but typical example is given. It consists in finding Pareto-optimal configurations for the motor drive of an electric vehicle. For that purpose, a geometric optimization method (i.e the Hooke and Jeeves minimization procedure) associated with an objective weighting sum and a Multiobjective Genetic Algorithm (i.e. the NSGA-II) are compared. Several performance issues are discussed such as the accuracy in the determination of Pareto-optimal configurations and the capability to well spread these solutions in the objective space

A review of design optimization methods for electrical machines

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. Electrical machines are the hearts of many appliances, industrial equipment and systems. In the context of global sustainability, they must fulfill various requirements, not only physically and technologically but also environmentally. Therefore, their design optimization process becomes more and more complex as more engineering disciplines/domains and constraints are involved, such as electromagnetics, structural mechanics and heat transfer. This paper aims to present a review of the design optimization methods for electrical machines, including design analysis methods and models, optimization models, algorithms and methods/strategies. Several efficient optimization methods/strategies are highlighted with comments, including surrogate-model based and multi-level optimization methods. In addition, two promising and challenging topics in both academic and industrial communities are discussed, and two novel optimization methods are introduced for advanced design optimization of electrical machines. First, a system-level design optimization method is introduced for the development of advanced electric drive systems. Second, a robust design optimization method based on the design for six-sigma technique is introduced for high-quality manufacturing of electrical machines in production. Meanwhile, a proposal is presented for the development of a robust design optimization service based on industrial big data and cloud computing services. Finally, five future directions are proposed, including smart design optimization method for future intelligent design and production of electrical machines

Efficiency Optimization and Control of Permanent Magnet Synchronous Brushless Motors in Three-Phase Pulse Width Modulated Voltage Source Inverter Drives

In high performance drives where it is desirable to exploit the usefulness of reluctance torque and machine saliency, permanent magnet synchronous brushless motors are machines of choice. However, speed control of these machines especially in the flux weakening region becomes more complex due to the non-linear coupling among the winding currents as well as the nonlinearity present in the torque. While numerous research efforts in the past have considered control and efficiency improvements of induction motors, and synchronous motors with field windings, research efforts in developing an efficiency optimization and control strategy applicable to all salient-type permanent magnet synchronous brushless motors are still in their infancy.;A traditional control technique that has commonly been employed in efficiency improvement efforts is the stator\u27s zero d-axis current (i ds=0) technique. In this method, the rotor flux is aligned with the direct-axis so that the stator\u27s direct-axis current is zero and the torque becomes a linear function of the stator\u27s quadrature-axis current. Although this method achieves decoupling of winding currents and simplicity of control, it does not fully exploit the use of the machine\u27s saliency and reluctance torque, and is also not well-suited for wide-range load operations. The maximum torque per ampere (MTPA) technique is another less complex technique that has been considered which fully exploits the use of machine saliency with motor torque selected along the geometric curve of minimum-amplitude current space vectors for minimum loss operation. The drawback of the MTPA technique is that it does not provide high efficiency performance for synchronous reluctance motors running at low fractional loads.;In this work, the problem of efficiency optimization in the salient-type permanent magnet synchronous brushless motors is investigated. A machine model which includes the effect of core losses is proposed for developing a loss minimization algorithm that dynamically determines the optimal reference currents and voltages required for minimizing the total electrical losses (copper losses and core losses) within the feasible operating regions imposed by the motor and inverter capacities. The loss minimization strategy is implemented within a speed control loop for a synchronous reluctance motor drive and the effectiveness of the proposed scheme is validated by comparing performances with that of the traditional maximum torque per ampere and stator\u27s zero d-axis current vector control methods. It is shown that the proposed scheme offers the advantages of simplicity and superior performance throughout the entire operating range, and also improves motor efficiency to 96% at full load and full-speed operating condition

Design Synthesis and Optimization of Permanent Magnet Synchronous Machines Based on Computationally-Efficient Finite Element Analysis

In this dissertation, a model-based multi-objective optimal design of permanent magnet ac machines, supplied by sine-wave current regulated drives, is developed and implemented. The design procedure uses an efficient electromagnetic finite element-based solver to accurately model nonlinear material properties and complex geometric shapes associated with magnetic circuit design. Application of an electromagnetic finite element-based solver allows for accurate computation in intricate performance parameters and characteristics. The first contribution of this dissertation is the development of a rapid computational method that allows accurate and efficient exploration of large multi-dimensional design spaces in search of optimum design(s). The computationally efficient finite element-based approach developed in this work provides a framework of tools that allow rapid analysis of synchronous electric machines operating under steady-state conditions. In the developed modeling approach, major steady-state performance parameters such as, winding flux linkages and voltages, average, cogging and ripple torques, stator core flux densities, core losses, efficiencies and saturated machine winding inductances, are calculated with minimum computational effort. In addition, the method includes means for rapid estimation of distributed stator forces and three-dimensional effects of stator and/or rotor skew on the performance of the machine. The second contribution of this dissertation is the development of the design synthesis and optimization method based on a differential evolution algorithm. The approach relies on the developed finite element-based modeling method for electromagnetic analysis and is able to tackle large-scale multi-objective design problems using modest computational resources. Overall, computational time savings of up to two orders of magnitude are achievable, when compared to current and prevalent state-of-the-art methods. These computational savings allow one to expand the optimization problem to achieve more complex and comprehensive design objectives. The method is used in the design process of several interior permanent magnet industrial motors. The presented case studies demonstrate that the developed finite element-based approach practically eliminates the need for using less accurate analytical and lumped parameter equivalent circuit models for electric machine design optimization. The design process and experimental validation of the case-study machines are detailed in the dissertation

Magnetic noise reduction of in-wheel permanent magnet synchronous motors for light-duty electric vehicles

This paper presents study of a multi-slice subdomain model (MS-SDM) for persistent low-frequency sound, in a wheel hub-mounted permanent magnet synchronous motor (WHM-PMSM) with a fractional-slot non-overlapping concentrated winding for a light-duty, fully electric vehicle applications. While this type of winding provides numerous potential benefits, it has also the largest magnetomotive force (MMF) distortion factor, which leads to the electro-vibro-acoustics production, unless additional machine design considerations are carried out. To minimize the magnetic noise level radiated by the PMSM, a skewing technique is targeted with consideration of the natural frequencies under a variable-speed-range analysis. To ensure the impact of the minimization technique used, magnetic force harmonics, along with acoustic sonograms, is computed by MS-SDM and verified by 3D finite element analysis. On the basis of the studied models, we derived and experimentally verified the optimized model with 5 dBA reduction in A-weighted sound power level by due to the choice of skew angle. In addition, we investigated whether or not the skewing slice number can be of importance on the vibro-acoustic objectives in the studied WHM-PMSM.Postprint (published version

Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine

Optimal performance of the electric machine/drive system is mandatory to improve the energy consumption and reliability. To achieve this goal, mathematical models of the electric machine/drive system are necessary. Hence, this motivated the editors to instigate the Special Issue “Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine”, aiming to collect novel publications that push the state-of-the art towards optimal performance for the electric machine/drive system. Seventeen papers have been published in this Special Issue. The published papers focus on several aspects of the electric machine/drive system with respect to the mathematical modelling. Novel optimization methods, control approaches, and comparative analysis for electric drive system based on various electric machines were discussed in the published papers

Advancements in Flux Switching Machine Optimization : Applications and Future Prospects

This work was supported by the Commonwealth Scholarship Commission, U. K., under Grant Number: NGCN-180-2021Peer reviewe