Optimal Rotor Structure Design of Interior Permanent Magnet Synchronous Machine based on Efficient Genetic Algorithm Using Kriging Model

This paper describes an optimal design process to achieve a high-performance Interior Permanent Magnet Synchronous Machine (IPMSM) for electric spindle, focusing on the torque density and torque ripple. After the design of initial model, some detailed parameters, such as slot-opening width, depth of permanent magnet (PM) and shape of flux-barrier, are optimized. Moreover, in order to reduce the torque ripple, several methods, which include step-skewed rotor method, slot skewing method and auxiliary slot method, are analyzed and discussed, and some comparison of these methods is displayed. The simulation and analysis are accomplished using 2D-FEM. At last, the design of an IPMSM with high torque density and low torque ripple is accomplished. Prototypes will be fabricated to verify the validity of the proposed design.

In this paper, an outer rotor interior permanent magnet synchronous machine (IPMSM) with hybrid permanent magnet (PM) material is proposed. The key is to adopt the outer rotor structure with two-layer crescent barriers and hybrid PM material to maximize the output torque and reduce the usage of high-cost rare-earth PM. The ferrite PMs are filled in the middle of the crescent barriers with thicker thickness, while the rare-earth PMs are filled into the bilateral of the crescent barriers with thinner thickness. To verify the effectiveness of the proposed rotor structure, optimizations are first carried out among the conventional rotor structures with single kind of PM material and the proposed rotor structure with hybrid PMs. Then, detailed comparisons have been investigated. Results indicate that the proposed machine has higher torque density than the machine with only ferrite PM and can reduce almost half the usage of rare-earth PM in comparison to the machine with only rare-earth PM. Moreover, the proposed rotor structure is further optimized considering productivity.

Permanent magnet synchronous machines (PMSMs) have been used in various applications owing to the high power density of the magnets. Especially interior permanent magnet synchronous machines (IPMSMs) are attractive in high power density applications since IPMSMs can generate both magnet torque and reluctance torque, and the field weakening control can reduce the output voltage.However, a lot of field weakening current is required to generate a lot of reluctance torque, the carefully magnet design, the thick magnet is used, is needed not to demagnetize the magnet. Hence, the cost of the magnet increases and the operating temperature is limited.In this paper, a field intensified IPMSM (FIIPM) is proposed. The proposed FIIPM has a forward saliency and the positive current on the direct axis is added in order to the magnet to generate a reluctance torque. The technique of adding the positive current contributes the magnet not to demagnetize, and using a thick magnet to protect from the demagnetization is not necessary.This paper shows that IPMSMs are difficult to generate more reluctance torque than magnet torque by using a relationship between saliency and torque ratio. The FIIPM is introduced as a possible design option for high reluctance torque machine. The general characteristics of FIIPMs are analyzed using finite element analysis (FEA).

This paper develops a genetic-PI based controller for interior permanent magnet synchronous motor (IPMSM) drive. An artificial neural network (ANN) is used for on-line tuning of the PI controller. Genetic algorithm (GA) has been used in this work in order to obtain the optimized values of the PI controller parameters for precise speed control under different operating conditions over wide speed range. The performance index which has been utilized as GA objective function is zero steady-state error, minimum speed deviation, and minimum settling time of the IPMSM drive. The optimal behavior of drive can be achieved by considering two control strategics: maximum torque per ampere (MTPA) control strategy in constant torque region and flux-weakening control strategy in constant power region. In developing the proposed controller, the PI controller parameters are optimized by GA at all operating conditions, in a closed loop vector control scheme. By obtaining the parameters at a number of points in the possible operating region, a look-up table approach has been completed. Then an ANN is trained by this look-up table. Ultimately, the well-trained ANN is utilized for on-line tuning of the PI controller parameters to ensure optimum drive performance under different disturbances and operating conditions over wide speed range.

PurposeThis paper aims to present an interior permanent magnet synchronous machine (IPMSM) with double-layer PMs used for electric vehicles, of which the integrated simulation of electromagnetic field, stress field and temperature field are analyzed.Design/methodology/approachSome electromagnetic characteristics including iron loss, efficiency and flux linkage are obtained by finite element analysis. The mechanical strength of rotor at the maximum speed and the temperature rise at the rated load are calculated by three-dimensional finite element analysis (FEA).FindingsThe results show that the presented IPMSM can work with sufficient mechanical strength, machine temperature rise and high efficiency during field-weakening operation. The experiments were carried out to verify the FEA, and acceptable results can be achieved.Originality/valueThis paper proposed a novel IPMSM with the double-layer permanent magnets, which is designed and checked by the multi-physics fields, and the high efficiency in all operational regions can be achieved for this machine.

This paper presents a detailed process for the design of interior permanent magnet synchronous machines (IPMSMs) for electric vehicle (EV) applications. First, a comprehensive design process featuring two objectives and three constraints is proposed to realize an optimal IPMSM design that can satisfy the key performance requirements for an EV application. The objectives and constraints were carefully selected and designed to obtain a balance between performance, efficiency, and cost. Because the inductances and magnet flux linkage of the machine are key design parameters for attaining optimal flux-weakening capability, the impact of the machine dimensions on these two parameters is thoroughly investigated and explained using both analytical and numerical techniques. Additional analyses including normalized key performance metrics and the impact of short-circuit faults in PM machines with three different characteristic current values (1, 1.3, and 2.6 pu) are also provided, highlighting the advantages and limitations of the three baseline designs.

With designing stator teeth by using grain oriented silicon sheets (GO) and other parts still with non-grain oriented silicon sheets (NGO), the electromagnetic performance of interior permanent magnet synchronous machine (GO-IPMSM) can be improved greatly, however its torque ripple will be increased as well. For reducing its torque ripple, optimizing its rotor barrier shape is an effective way. In this paper, the polynomial method is proposed to establish the rotor barrier shape, and the genetic algorithm (GA) method is employed for the optimization process. In case the optimized GO-IPMSM can work normally, its anti irreversible demagnetization ability is analyzed as well. As shown, with the GO is adopted for designing the stator teeth and its rotor barrier shape is optimized, though its torque ability and efficiency have been increased, its anti irreversible demagnetization risk ability is reduced, however the proposed machine can still operate safely.

A novel asymmetric delta‐type and Spoke‐type interior permanent magnet synchronous machine (ASD‐IPM) is proposed for electric vehicles (EVs) application that uses the magnetic field shifting technique to maximise the average torque and lessen torque ripples. The proposed ASD‐IPM is deduced from the conventional asymmetric spoke and V‐shape IPM by attaching additional asymmetric flux barriers (AFB) to the left side of the spoke‐type PMs and to the other side of the delta‐type PMs. This configuration helps in reducing the leakage flux and achieving good flux concentration. The proposed design is optimised through a Genetic Algorithm (GA) to investigate the electromagnetic performances at no‐load and on‐load conditions. Also, the efficiency maps of both the proposed design and conventional design are analysed and compared. The results show that the proposed ASD‐AIPM has superior efficiency and a favorable torque profile, making it a suitable choice for electric vehicle applications. Furthermore, the proposed design is rescaled to the Toyota Prius 2010 design, with the only change in the slot/pole pair combination due to the presence of spoke‐PMs in the proposed design. The proposed ASD‐IPM achieves 7% higher torque than the existing Toyota Prius 2010 model. The efficiency maps of the rescaled design are also analysed and compared.

The main feature of an interior permanent magnet synchronous motor (IPMSM) is the reluctance torque, which increases the difficulty of regulating the motor current and torque. This is because the inductance of the stator across the air gap is not equal and vice versa in the surface-mounted PMSM. Thus, the field-oriented control (FOC) strategies of surface-mounted type is greatly desirable to the IPMSM. In this paper, some contributions of the FOC strategy are proposed. The primary objective is to achieve a high dynamic performance of the IPMSM in the region of flux-weakening under sudden torque turbulence and velocity fluctuation. The concentration of the proposed strategy is on the cost function of the parameter optimization, which is optimized based on a genetic algorithm to obtain parameters that will contribute to further driving stability in this region. Meanwhile, the improvement includes adjusting the saturation limits for the outer control loops to cancel the wave overshoots. Finally, the results of simulation and experimentation have fully verified the proposed approach. When compared to the classical strategy, the proposed algorithms can help decrease the settling time and the overshoot in both velocity and current.

This paper presents an automated design employed genetic algorithm (GA) to optimize non-overshoot PI speed and current controllers of interior permanent magnet synchronous motor (IPMSM). The drive control system is designed on the basis of vector control scheme incorporated with the maximum torque per ampere (MTPA) control strategy to improve the drive performance. A method is given for designing controllers to track the step references with zero overshoot response under a constant load torque. Simulation and experimental results verify the effectiveness of the proposed method.

To analyze the impact of cobalt iron cores in the design of interior permanent magnet synchronous motors (IPSM) for competition electric vehicles, a spoke-type IPSM geometry is optimized considering FeSi and VaCoFe cores. This optimization is done for a range of torque/efficiency, to provide a general comparative analysis between materials considering the application of a FormulaStudent 4-motor competition car’s powertrain. A genetic optimization algorithm (NSGA-II) is applied over a hybrid analytical/finite-element model of the motor to provide sufficiently accurate electromagnetic and thermal results within a feasible time. It is shown that machines with VaCoFe core are a better alternative across both considered torque and efficiency ranges. VaCoFe can result in an estimated increase of up to 3% in efficiency for the same torque, or up to 70% torque increase for the same efficiency level. However, because of the density difference between materials, core weight is similar for the overlapping torque range. For the competition car, with a required 20Nm of nominal torque, there is an efficiency increase of 1.7% and a reduction of 11% in core volume for the motor with VaCoFe compared to FeSi.

The use of a cobalt-iron (VaCoFe) core is investigated as an alternative to silicon-iron (FeSi) in the design of interior permanent magnet synchronous motors (IPMSM). Considering VaCoFe and FeSi cores, a spoke-type IPMSM geometry is optimized for a torque range up to 40 N·m, providing a general comparative analysis between materials. This is done considering the application of a four-motor competition vehicle’s powertrain. A genetic optimization algorithm is coupled to the motor’s electromagnetic and thermal hybrid analytical/finite-element model to provide sufficiently accurate results within a feasible time. VaCoFe allows an estimated increase of up to 64% in torque for the same efficiency level, or up to 5% in efficiency for the same torque. After optimization and using a detailed time-dependent model, a potential 3.2% increase in efficiency, a core weight reduction of 4.1%, and a decrease of 9.6% in the motor’s core volume were found for the VaCoFe at 20 N·m. In addition, for the same motor volume, the VaCoFe allows an increase of 51.9% in torque with an increase of 1.1% in efficiency when compared with FeSi.

This paper presents the implementation of an electrical machine design tool including its overall architecture. The tool is flexible and can be employed for the sizing of any permanent magnet synchronous machine. The case study considered in this work is the design of V-shaped interior permanent magnet synchronous machine for automotive applications. The preliminary design stage is considered with the aim of selecting the optimum machine pole pairs number and rotation speed. A multi-objective genetic algorithm is linked to the design tool and adopted to maximize the machine power density in terms of kW/L as well as to minimize the machine cost. The outcomes of this work are showing the variation of the above objective functions with respect to the pole-pair number and gearbox ratio as well as their effect on the machine efficiency.

Eccentricity is a common mechanical fault in electrical machine operation. In this paper, we have proposed a magnetic equivalent circuit (MEC) model considering magnetic saturation to evaluate and analyse the performance of an interior permanent magnet synchronous machine (PMSM) under eccentricity fault. This model provides the advantages in fast computation while giving reasonable degree of accuracy. The potential application of this model includes fault tolerant machine design optimization, fault tolerant machine drive design, as well as fault diagnosis and monitoring. The accuracy of this model will be gauged by comparison with finite element method (FEM) modeling.

This paper compares two types of interior permanent magnet synchronous motors (IPMSMs) to determine the most effective arrangement for electric vehicle (EV) applications. The comparison is based on torque ripple, power, efficiency, and mechanical objectives. The study introduces a novel technique that optimizes notching parameters in a selected motor topology by inserting a ship-shaped notch into the bridge area between double U-shaped layers. In addition, this study presents two comprehensive approaches of robust combinatorial optimization that are used in machines for the first time. In the first approach, modeling is performed to identify important variables using Pearson Correlation and the mathematical model of the Anisotropic Kriging model from the Surrogate model. Then, in the second approach, the proposed algorithm, Multi-Objective Genetics Algorithm (MOGA), and Surrogate Quadratic Programming (SQP) are combined and implemented on the Anisotropic Kriging model to choose a robust model with minimum error. The algorithm is then verified with FEM results and compared with other conventional optimization algorithms, such as the Genetics Algorithm (GA) and the Particle Swarm Optimization algorithm (PSO). The motor characteristics are analyzed using the Finite Element Method (FEM) and global map analysis to optimize the performance of the IPMSM for EV applications. A comparative study shows that the enhanced PMSM developed through the optimization process demonstrates superior performance indices for EVs.