Multiobjective System Level Optimization Method for Switched Reluctance Motor Drive Systems Using Finite-Element Model

Diao, Kaikai; Sun, Xiaodong; Lei, Gang; Guo, Youguang; Zhu, Jun

doi:10.1109/tie.2019.2962483

Cited by 113 publications

(39 citation statements)

References 34 publications

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“…The conventional component-level (e.g., the motor) optimization cannot guarantee optimal performance of the whole system. To design and optimize this kind of drive systems, electromagnetic analysis, thermal analysis, mechanical analysis, power electronics, and control systems have to be investigated in the optimization [102][103][104][105][106][107][108][109][110]. Therefore, multidisciplinary design optimization methods should be investigated.…”

Section: System-level Multidisciplinary Design Optimizationmentioning

confidence: 99%

Machine Learning for Design Optimization of Electromagnetic Devices: Recent Developments and Future Directions

Lei

Bramerdorfer

et al. 2021

Applied Sciences

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This paper reviews the recent developments of design optimization methods for electromagnetic devices, with a focus on machine learning methods. First, the recent advances in multi-objective, multidisciplinary, multilevel, topology, fuzzy, and robust design optimization of electromagnetic devices are overviewed. Second, a review is presented to the performance prediction and design optimization of electromagnetic devices based on the machine learning algorithms, including artificial neural network, support vector machine, extreme learning machine, random forest, and deep learning. Last, to meet modern requirements of high manufacturing/production quality and lifetime reliability, several promising topics, including the application of cloud services and digital twin, are discussed as future directions for design optimization of electromagnetic devices.

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Section: System-level Multidisciplinary Design Optimizationmentioning

confidence: 99%

Machine Learning for Design Optimization of Electromagnetic Devices: Recent Developments and Future Directions

Lei

Bramerdorfer

et al. 2021

Applied Sciences

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“…7 (a), the 3D map of inductance based on RR-LSSVR model has been obtained. To estimate current i according to the flux linkage ψ and rotor position θ, the RR-LSSVR L(i, θ) model is transformed to ψ(i, θ) according to (4) and then converted to i(ψ,θ) by inverting the relationship between i and ψ by angle θ one by one. RR-LSSVR T(i, θ) block estimates the torque T according to the current i and rotor position θ.…”

Section: A Simulation Validationmentioning

confidence: 99%

“…WITCHED reluctance motors (SRMs) have been utilized widely in numerous industrial devices thanks to its advantages in structure, cost, and fault-tolerance [1]- [4]. However, the nonlinear characteristics in magnetic and torque make its torque calculation lack of reliability and accuracy [5,6].…”

Section: Introductionmentioning

confidence: 99%

Accurate torque modeling with PSO-based recursive robust LSSVR for a segmented-rotor switched reluctance motor

Sun

Zhu

2020

Trans. Electr. Mach. Syst.

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In order to improve the reliability in torque calculation of SRM, an accurate nonlinear torque model regresses by recursive robust least squares support vector regression (RR-LSSVR) is proposed in this paper. The model is in terms of a segmented-rotor switched reluctance motor (SSRM). The characteristics of the SSRM is introduced to show its nonlinear characteristics both in magnetic and torque. Then, its mathematic model is established, and an accurate inductance measurement method and a torque calculation method are presented. After this, the principle of the RR-LSSVR and why it can adjust weights according to errors are described. The model used the RR-LSSVR algorithm shows an outstanding capability in accuracy and quickness compared with other algorithms. Finally, to further validate the accuracy of the proposed model in practical application, simulation and experiment are designed based on a 16/10 SSRM.

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“…For some applications, increase the phase number is a simple and effective method to decrease the torque ripple, reduce each phase current, and improve fault-tolerance of drive system [10][11][12]. So far the research results of multi-phase SRMs are mainly focused on four-phase SRM drive systems [13][14]. While in recent years, researches related to five-phase and six-phase SRMs are also increasing [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Midpoint Current Characteristics for Novel Six-Phase N+2 Power Converter in Different Working Condition

et al. 2020

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In this paper, a novel N+2 power converter is introduced and be applied to a six-phase switched reluctance motor (SRM) drive system. Compared with six-phase asymmetric half bridge (AHB) converter, the number of power devices required by this N+2 converter is greatly reduced, while the independence and controllability of each phase can be ensured. However, in N+2 converters, the two midpoint switches are also important components and working at much higher switching frequency than phase switches. The value of the midpoint current directly affects the heating problem of these midpoint switches then affects the reliability of the N+2 converter. Hence, different operate modes of multi-phase excitation state of N+2 converter are enumerated to obtain the relation between the midpoint current and phase currents. Then the characteristics of the midpoint current under different control parameters were obtained through MATLAB-Simulink, and the parameter optimization rules for reducing the amplitude of midpoint current are summarized. In addition, the characteristics of midpoint current in several typical fault states are also summarized. Finally, the simulation results are verified by experiments.

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Multiobjective System Level Optimization Method for Switched Reluctance Motor Drive Systems Using Finite-Element Model

Cited by 113 publications

References 34 publications

Machine Learning for Design Optimization of Electromagnetic Devices: Recent Developments and Future Directions

Machine Learning for Design Optimization of Electromagnetic Devices: Recent Developments and Future Directions

Accurate torque modeling with PSO-based recursive robust LSSVR for a segmented-rotor switched reluctance motor

Analysis of Midpoint Current Characteristics for Novel Six-Phase N+2 Power Converter in Different Working Condition

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