Optimization of BLDC Motor Geometry using Particle Swarm Optimization Algorithm to Achieve Efficiency Balance Across Various Electric Vehicle Traction Requirements

Abstract

Gasoline vehicles (GVs) contribute significantly to global energy crises and environmental pollution, while electric vehicles (EVs) offer a more sustainable alternative. However, the current development and deployment of EVs are largely limited to ideal operating conditions, such as urban roads. To compete effectively with GVs, EVs must have drivetrain systems that maintain high efficiency even in non-ideal environments, including rural areas and rough terrains. This study proposes a geometry optimization method for a 1 kW Brushless DC (BLDC) motor to improve energy efficiency under three primary EV traction scenarios: climbing, acceleration, and cruising. The optimization targets nine geometric parameters—outer and inner stator radius, magnet thickness, rotor yoke thickness, shoe stator thickness, magnet width, shoe stator width, stator pole width, and back-iron thickness. The optimization is performed using a Particle Swarm Optimization (PSO) algorithm integrated with Finite Element Method Magnetics (FEMM) and analytical performance evaluation. The optimization constraints are derived from traction dynamics, weight, and volume limitations based on the regulations of the Indonesian Electric Vehicle Competition (Kompetisi Mobil Listrik Indonesia, KMLI). The results show that the optimized BLDC motor geometry can increase efficiency by up to 24.3% and torque by 11.3% compared to the baseline design. This research contributes a high-efficiency BLDC motor design tailored for dynamic EV traction demands under regulatory and extreme operational constraints, making it highly suitable for further development, including additional performance scenarios such as deceleration and cornering.

Keywords

Electric vehicle; BLDC motor; energy efficiency; geometry optimization; PSO algorithm.

References

Z. Yan, H. Ding, and L. Chen, “The analyzing the role of electric vehicles in urban logistics: A case of China,” Front. Environ. Sci., vol. 11, Art. no. 1128079, 2023. http://dx.doi.org/10.3389/fenvs.2023.1128079

S. Ma, K. Chen, and Q. Zhang, “Analysis of multi-objective optimization design of interior double radial and tangential combined magnetic pole permanent magnet drive motor for electric vehicles,” World Electr. Veh. J., vol. 15, Art. no. 142, 2024. http://dx.doi.org/10.3390/wevj15040142

R. Kumar, “Electric vehicle adoption in urban areas: socio-economic factors and policy implications,” Shodh Sagar Journal of Electric Vehicles, vol. 1, no. 2, pp. 14–19, 2024. http://dx.doi.org/10.36676/jev.v1.i2.11

J. Ma et al., “Analysis of urban electric vehicle adoption based on operating costs in urban transportation network,” Systems, vol. 11, no. 3, Art. no. 149, 2023. http://dx.doi.org/10.3390/systems11030149

Z. Pusztai, P. Kőrös, F. Szauter, and F. Friedler, “Implementation of optimized regenerative braking in energy efficient driving strategies,” Energies, vol. 16, no. 6, Art. no. 2682, 2023. http://dx.doi.org/10.3390/en16062682

E. Håkansson and B. Dubé, “Winning approach: selection criteria for competitive battery powered racing vehicles,” World Electr. Veh. J., vol. 8, no. 1, pp. 160–171, 2016. http://dx.doi.org/10.3390/wevj8010160.

Marwansyah, Panduan Kompetisi Mobil Listrik Indonesia XIII – 2024 [Guide to the Indonesian Electric Car Competition XIII - 2024], Bandung, Indonesia: KMLI, 2024. [Online]. Available: https://kmli.polban.ac.id/panduan-kmli-xiii/. Accessed: Aug. 25, 2025. (in Indonesian)

O. Tosun, K. Toker, O. Tosun, N. F. O. Serteller, and V. Topuz, “The design, optimization, and experimental study of hub and axial flux BLDC motor under operating conditions for light electric vehicles,” Adv. Sci. Technol. Eng. Syst. J., vol. 8, no. 3, pp. 272–282, 2023. http://dx.doi.org/10.25046/aj080330

B. Azhari, P. Irasari, and P. Widianto, “Design and simulation of 5 kW BLDC motor with half-buried permanent magnets using an existing stator body,” Int. J. Power Electron. Drive Syst., vol. 12, no. 4, pp. 2030–2043, 2021. http://dx.doi.org/10.11591/ijpeds.v12.i4.pp2030-2043.

C. Kumar, D. M. Mary, and T. Gunasekar, “MOCHIO: a novel multi-objective coronavirus herd immunity optimization algorithm for solving brushless direct current wheel motor design optimization problem,” Automatika, vol. 63, no. 1, pp. 149–170, 2022. http://dx.doi.org/10.1080/00051144.2021.2014035

A. Kerem, “Design, implementation and speed estimation of three-phase 2 kW out-runner permanent magnet BLDC motor for ultralight electric vehicles,” Electr. Eng., vol. 103, no. 5, pp. 2547–2559, 2021. http://dx.doi.org/10.1007/s00202-021-01279-5.

Z. Arifin, I. W. Adiyasa, and M. A. H. Rasid, “Design optimization analysis on the performance of BLDC motors on electric bicycles,” J. Phys.: Conf. Ser., vol. 2406, Art. no. 012016, 2022. http://dx.doi.org/10.1088/1742-6596/2406/1/012016

H. Msaddek, A. Mansouri, and H. Trabelsi, “Optimal design and cogging torque minimization of a permanent magnet motor for an electric vehicle,” Teh. Vjesn., vol. 30, no. 2, pp. 538–544, 2023. http://dx.doi.org/10.17559/TV-20220815140808.

M. Sundaram et al., “Design and FEM analysis of high-torque power density permanent magnet synchronous motor (PMSM) for two-wheeler e-vehicle applications,” Int. Trans. Electr. Energy Syst., vol. 2022, Art. ID 1217250, 14 pp., 2022. http://dx.doi.org/10.1155/2022/1217250

M. As-salaf and Syahrial, “Simulasi Pengaturan Kecepatan Motor BLDC menggunakan Software PSIM [Simulation of BLDC Motor Speed Control using PSIM Software],” MIND J., vol. 6, no. 1, pp. 103–117, 2021. https://doi.org/10.26760/mindjournal.v6i1.103 (in Indonesian)

S. Torabi, M. Bellone, and M. Wahde, “Energy minimization for an electric bus using a genetic algorithm,” Eur. Transp. Res. Rev., vol. 12, no. 1, p. 6, 2020. http://dx.doi.org/10.1186/s12544-019-0393-1

K. N. Genikomsakis and G. Mitrentsis, “A computationally efficient simulation model for estimating energy consumption of electric vehicles in the context of route planning applications,” Transp. Res. D, vol. 50, pp. 98–118, 2017. http://dx.doi.org/10.1016/j.trd.2016.10.014

O. Ustun, G. Tanc, O. C. Kivanc, and G. Tosun, “In pursuit of proper BLDC motor design for electric bicycles,” in Proc. 2016 22nd Int. Conf. Electr. Mach. (ICEM), 2016, pp. 1808–1814. http://dx.doi.org/10.1109/ICELMACH.2016.7732769

V. Bogdan, M. Adrian, L. Leonard, B. Alexandra, S. Alecsandru, and N. Ionut, “Design and optimization of a BLDC motor for small power vehicles,” in Proc. SIELMEN 2021—11th Int. Conf. Electromech. Energy Syst., 2021, pp. 438–443. http://dx.doi.org/10.1109/SIELMEN53755.2021.9600327.

Y. Cheng, X. Lyu, and S. Mao, “Optimization design of brushless DC motor based on improved JAYA algorithm,” Sci. Rep., vol. 14, Art. no. 5427, 2024. http://dx.doi.org/10.1038/s41598-024-54582-z

Y. U. Nugraha, A. Cahyadi, M. N. Yuniarto, and I. Sidharta, “Design optimization for torque density in brushless DC motor with IPM V-type using PSO method,” IOP Conf. Ser.: Mater. Sci. Eng., vol. 694, Art. no. 012009, 2019. http://dx.doi.org/10.1088/1757-899X/694/1/012009

http://dx.doi.org/10.28989/avitec.v7i3.3119

Article Metrics

Abstract view: 23 times

This work is licensed under a Creative Commons Attribution 4.0 International License.

Refbacks

• There are currently no refbacks.