Simultaneous optimization of geometry and firing angles of in-wheel switched reluctance motor

Anvari, Bahareh; Toliyat, H.A.

doi:10.1109/ecce.2017.8095861

Cited by 11 publications

(4 citation statements)

References 21 publications

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“…Algorithms such as GA, differential evolution algorithm, particle swarm optimization algorithm or others are generally used as minimum or maximum single objective in solving optimization problems. However, the optimization problems especially electric motor designs may be more suitable for multi-objective [23][24]. In this case, it is inevitable to obtain solutions for each objective and a single solution that is best for all objectives may not be available.…”

Section: Multi-objective Optimization Algorithmsmentioning

confidence: 99%

An approach based on non-dominated sorting genetic algorithm III for design of permanent magnet synchronous motor

Mutluer¹

2020

ijisae

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Today due to industrial developments, the use of electric motors has increased in all fields. The increase also preceded the development of higher-specification motors. Although weight, cogging torque, torque ripples and drive technology etc. for the working area are important, the demand for the production of highly efficient and cost-effective motors has risen further due to the energy phenomenon in the world. High-quality algorithms are needed to achieve these objectives as well, because electric motor designs are multiparameter and nonlinear engineering problems. This study aims to provide a multi-purpose intelligent design with NSGAII and NSGAIII by selecting outputs such as efficiency and cost of permanent magnet synchronous motor as an objective function. The design was intended for low speed and high torque/volume applications and the motor geometry was thus chosen as surface-mounted and double-layer concentrated winding. The optimization results were tested with a finite element program. Both methods resulted in a 3% increase in efficiency and a 37% reduction in cost versus initial design. Also, according to the results obtained, although NSGA-II and NSGA-III achieved similar results, NSGA-III results showed a more robust and stable course than NSGA-II results. The compatibility of the design optimization and the results of numerical analysis are acceptable and highly satisfactory. So, it provides outputs to demonstrate the features of an electric motor design optimization.

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Section: Multi-objective Optimization Algorithmsmentioning

confidence: 99%

An approach based on non-dominated sorting genetic algorithm III for design of permanent magnet synchronous motor

Mutluer¹

2020

ijisae

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“…The selection of optimal parameters when designing an electric machine is a multidimensional and multimodal optimization problem, which additionally requires the use of high-performance computers. Moreover, the design process of an electric machine requires calculation of several parameters whose values are mutually dependent, which tends to complicate the optimization calculations [23,37,[51][52][53][54][55][56]. The methodology for the design and analysis of ERPMSM parameters has been implemented based on the diagram presented in Figure 2.…”

Section: Motor Design Considerationsmentioning

confidence: 99%

Design, Analysis of the Location and Materials of Neodymium Magnets on the Torque and Power of In-Wheel External Rotor PMSM for Electric Vehicles

Łebkowski

2018

Energies

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The technology of mounting electric direct drive motors into vehicle wheels has become one of the trends in the field of electric vehicle drive systems. The article presents suggestions for answering the question: How should magnets be mounted on the External Rotor Permanent Magnet Synchronous Machine (ERPMSM) with three phase concentrated windings, to ensure optimal operation of the electric machine in all climatic and weather conditions? The ERPMSM design methodology is discussed. Step by step, a method related to the implementation of subsequent stages of design works and tools (calculation methods) used in this type of work are presented. By means of FEM 2D software, various ERPMSM designs were analyzed in terms of power, torque, rotational speed, cogging torque and torque ripple. The results of numerical calculations related to variations in geometric sizes and application of different base materials for each of ERPMSM machine components are presented. The final parameters of the motor designed for mounting inside the wheel of the vehicle are presented (Power = 53 kW, Torque = 347 Nm; Base speed = 1550 RPM), which correspond to the adopted initial assumptions.

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“…Multi-objective optimization, as one of the means to promote the comprehensive output characteristics of SRM, which has been widely concerned and studied by a large number of scholars in recent years (Anvari and Toliyat, 2017; Chen et al, 2018a, 2018b). Ma and Qu (2015) took maximizing torque per active mass, maximizing efficiency, and minimizing torque ripple as the optimization objectives.…”

Section: Introductionmentioning

confidence: 99%

Modeling and suppression of unbalanced radial force for in-wheel motor driving system

Deng

Liu

et al. 2021

Journal of Vibration and Control

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Considering the negative vertical dynamics effect of switched reluctance motor on an in-wheel motor driving system, this article presents a modeling and suppression method for unbalanced radial force of the in-wheel motor driving system. To tease out the coupling relationship within the in-wheel motor driving system, this investigation, respectively, explores the principle of unbalanced radial force and the coupling relationship between rotor eccentricity and road excitation based on the suspension response model with unbalanced radial force under road excitation. The switched reluctance motor nonlinear analytical model was fitted by the Fourier series, and its radial electromagnetic force was modeled and analyzed by the Maxwell stress tensor method. To mitigate the influence of radial electromagnetic force fluctuation and unbalanced radial force amplitude value under eccentricity condition on the in-wheel motor driving system, the elitist non-dominated sorting genetic algorithm was adopted to improve radial electromagnetic force fluctuation and unbalanced radial force amplitude value of the switched reluctance motor. The simulation results show that the proposed optimization method can suppress the radial electromagnetic force fluctuation and unbalanced radial force amplitude value, and the negative effect of vertical dynamics of the in-wheel motor driving system is conspicuously mitigated.

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Simultaneous optimization of geometry and firing angles of in-wheel switched reluctance motor

Cited by 11 publications

References 21 publications

An approach based on non-dominated sorting genetic algorithm III for design of permanent magnet synchronous motor

An approach based on non-dominated sorting genetic algorithm III for design of permanent magnet synchronous motor

Design, Analysis of the Location and Materials of Neodymium Magnets on the Torque and Power of In-Wheel External Rotor PMSM for Electric Vehicles

Modeling and suppression of unbalanced radial force for in-wheel motor driving system

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