Torque ripple reduction by optimizing magnet shape using GA in axial gap motor

Abstract

This paper proposes a method to reduce torque ripple in axial gap motors by multi objective optimization of permanent magnets (PMs) shape using genetic algorithm (GA). Torque ripple is a problem because it causes vibration and noise. Conventionally, torque ripple has been reduced by quantitatively designing the PMs in the shape of multiplicative wave. However, it is difficult to optimize the objective function only by quantitative evaluation through sensitivity analysis. Therefore, in this study, the functions constituting the PMs interface shape are expressed as a Fourier-based series. The PMs is optimized by optimizing combination of their coefficients with GA. As a result, the proposed model is almost equal to the average torque of the basic model and the torque ripple is significantly reduced. Furthermore, fillets are applied and the effect on each characteristic is verified.

Keywords

Axial gap motor torque ripple genetic algorithm magnet shape Fourier-based series

Get full access to this article

View all access options for this article.

References

Watanabe

Saito

Ueno

Tsuruta

and Nakamura

, Thin and high-torque axial gap motor using soft magnetic powder cores, SEI Technical Review, No. 192, Jan. 2018, pp. 119–125.

Nishio

Yamauchi

Kondo

and Akatsu

, An injected high frequency current reference generation method for torque ripple reduction in PMSM, IEEJ Trans. on Industry Applications141(11) (2021), 848–855.

Zhang

Seidler

Dierken

and Doppelbauer

, Development of a yokeless and segmented armature axial flux machine, IEEE Trans. Ind. Electron.63(4) (2016), 2062–2071.

Tsunata

Takemoto

Ogasawara

Ueno

and Saitoh

, A proposal of ultra-flat axial gap motor employing C-type SMC core, in: IECON 45th Annual Conference of the IEEE Industrial Electronics Society, 2019, pp. 874–875.

Sato

Maejima

Kitagawa

and Takeshita

, Cogging torque reduction by using double skew of permanent magnets in axial gap motor, in: International Conference on Electrical Machines (ICEM), Valencia, Spain, 2022, pp. 212–218.

Sato

Maejima

Kitagawa

and Takeshita

, Shape optimization of permanent magnets considering multiplicative wave skew in axial gap motor, in: 2022 25th International Conference on Electrical Machines and Systems (ICEMS), Thailand, 2022, pp. 1–5.

Sugimoto

Kitagawa

and Takeshita

, Investigation of dimension reduction methods by multi-objective optimization for electromagnetic device with GP, in: 19th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering (ISEF), 2019.

Maejima

Kitagawa

and Takeshita

, Axial gap motor shape optimization using multi-objective based genetic programming technique, Journal of the Japan Society of Applied Electromagnetics and Mechanics31(2) (2023).

Kitagawa

Inaba

and Takeshita

, Objective function optimization for electrical machine by using multi-objective genetic programming and display method of its results, in: IEEJ Electronics Information and Systems Division Conference, 2018, pp. 1042–1047.

10.

Nazir

Ikram

Yousuf

Bukhari

S.S.H.

Shah

M.A.

Memon

A.A.

, Investigation of sinusoidal shaped rotor to reduce torque ripple in axial flux permanent magnet machine, International Journal of Ambient Energy43(1) (2022), 8113–8122.

11.

Huang

Kou

Zhao

Niu

and Zhang

, Multi-objective optimization design of a stator coreless multidisc axial flux permanent magnet motor, Energies15(13) (2022), 1–13.

12.

Anuja

T.A.

Arun Noyal Doss

Senthilkumar

Rajesh

K.S.

and Brindha

, Modification of pole pitch and pole arc in rotor magnets for cogging torque reduction in BLDC motor, IEEE Access10 (2022), 116709–116722.

13.

Wang

Qiu

and Yang

, A calculation method for the on-load cogging torque of permanent magnet synchronous machine, IEEE Access7 (2019), 106316–106326.