access icon free Multi-physics and multi-objective optimisation design of interior permanent magnet synchronous motor for electric vehicles

© The Institution of Engineering and Technology
Received 25/02/2020, Accepted 15/07/2020, Revised 26/06/2020, Published 17/07/2020

The electrical machine design method plays a decisive role in electric vehicles (EVs). However, only a few designs consider the coupling of multiple fields simultaneously. This study proposes an improved multi-physics and multi-objective optimisation design approach for designing a 75 kW interior permanent-magnet synchronous machine dedicated to EVs. Five optimal objectives including power density, temperature rise, price, torque ripple, and cogging torque are selected, and the first three objectives are optimised based on the sensitivity analysis of design parameters, where an improved thermal resistance network combining with finite-element analysis model is developed. Meanwhile, the torque ripple and cogging torque are involved in subsequent design optimisation. The temperature rise and structural strength are recalculated by using commercial finite-element model software, respectively, for validating the accuracy of optimisation design. Finally, a prototype motor is manufactured; both simulation and experimental results verify the feasibility and validity of the proposed optimisation design method.

Inspec keywords: thermal resistance; synchronous machines; permanent magnet machines; electric vehicles; torque; permanent magnet motors; optimisation; synchronous motors; finite element analysis

Other keywords: improved thermal resistance network; 75 kW interior permanent-magnet synchronous machine; electrical machine design method; multiobjective optimisation design approach; electric vehicles; temperature rise; power 75.0 kW; optimal objectives; cogging torque; finite-element analysis model; design parameters; optimisation design method; interior permanent magnet synchronous motor; subsequent design optimisation; improved multiphysics; finite-element model software; torque ripple

Subjects: Synchronous machines; Control of electric power systems; Transportation; Optimisation techniques; Numerical analysis; Finite element analysis

References

    1. 1)
      • 1. Yang, Y., Castano, S.M., Yang, R., et al: ‘Design and comparison of interior permanent magnet motor topologies for traction applications’, IEEE Trans. Electron., 2017, 3, (1), pp. 86–97.
    2. 2)
      • 4. Parasiliti, F., Villani, M., Lucidi, S., et al: ‘Finite-element-based multiobjective design optimization procedure of interior permanent magnet synchronous motors for wide constant-power region operation’, IEEE Trans. Ind. Electron., 2012, 59, (6), pp. 2503–2514.
    3. 3)
      • 21. Mellor, P.H., Roberts, D., Turner, D.R.: ‘Lumped parameter thermal model for electrical machines of TEFC design’, IEE Proc. B, 1991, 138, pp. 205–218.
    4. 4)
      • 11. Fang, G., Yuan, W., Yan, Z., et al: ‘Thermal management integrated with three-dimensional heat pipes for air-cooled permanent magnet synchronous motor’, Appl. Therm. Eng., 2017, 152, pp. 594–604.
    5. 5)
      • 18. Song, T., Zhang, Z., Liu, H., et al: ‘Multi-objective optimisation design and performance comparison of permanent magnet synchronous motor for EVs based on FEA’, IET Electr. Power Appl., 2019, 13, (8), pp. 1157–1166.
    6. 6)
      • 8. Chen, W., Ju, Y., Yan, D.: ‘Design and optimization of dual-cycled cooling structure for fully-enclosed permanent magnet motor’, Appl. Therm. Eng., 2019, 152, pp. 338–349.
    7. 7)
      • 7. Du, Y., Wang, X., Lv, H.: ‘Optimization of magnet shape based on efficiency map of IPMSM for EVs’, IEEE Trans. Appl. Supercond., 2016, 26, (7), pp. 1–7.
    8. 8)
      • 15. Xie, Y., Wang, Y.: ‘3D temperature field analysis of the induction motors with broken bar fault’, Appl. Therm. Eng., 2014, 66, pp. 25–34.
    9. 9)
      • 13. Ahn, K., Bayrak, A.E., Papalambros, P.Y.: ‘Electric vehicle design optimization: integration of a high-fidelity interior-permanent-magnet motor model’, IEEE Trans. Veh. Technol., 2015, 64, (9), pp. 3870–3877.
    10. 10)
      • 3. Jeong, C., Hur, J.: ‘Optimization design of PMSM with hybrid-type permanent magnet considering irreversible demagnetization’, IEEE Trans. Magn., 2017, 53, (11), pp. 1–4.
    11. 11)
      • 5. Hong, G., Wei, T., Ding, X.: ‘Multi-objective optimal design of permanent magnet synchronous motor for high efficiency and high dynamic performance’, IEEE Access, 2018, 6, pp. 23568–23581.
    12. 12)
      • 16. Zhao, W., Wei, X., Gerada, G., et al: ‘Multi-physics and multi-objective optimization of a high speed PMSM for high performance applications’, IEEE Trans. Magn., 2018, 54, (1), pp. 1–5.
    13. 13)
      • 9. Park, M.H., Kim, S.C.: ‘Thermal characteristics and effects of oil spray cooling on in-wheel motors in electric vehicles’, Appl. Therm. Eng., 2019, 152, pp. 582–593.
    14. 14)
      • 25. Zhu, X., Huang, J., Quan, L., et al: ‘Comprehensive sensitivity analysis and multi-objective optimization research of permanent magnet flux-intensifying motors’, IEEE Trans. Ind. Electron., 2019, 66, (4), pp. 2613–2626.
    15. 15)
      • 17. Ilka, R., Alinejad-Beromi, Y., Yaghobi, H.: ‘Techno-economic design optimisation of an interior permanent-magnet synchronous motor by the multi-objective approach’, IET Electr. Power Appl., 2018, 12, (7), pp. 972–978.
    16. 16)
      • 12. Bonthu, S.S.R., Choi, S., Baek, J.: ‘Design optimization with multiphysics analysis on external rotor permanent magnet-assisted synchronous reluctance motors’, IEEE Trans. Energy Convers., 2018, 33, (1), pp. 290–298.
    17. 17)
      • 24. Kulkarni, D.P., Rupertus, G., Chen, E.: ‘Experimental investigation of contact resistance for water cooled jacket for electric motors and generators’, IEEE Trans. Energy Convers., 2012, 27, (1), pp. 204–210.
    18. 18)
      • 26. Guruwatta Vidanalage, B.D., Toulabi, M.S., Filizadeh, S.: ‘Electromagnetic design optimization and sensitivity analysis for IPM synchronous motors’. IEEE ICIT, Toronto, 2017, pp. 288–293.
    19. 19)
      • 27. Cavazzuti, M., Gaspari, G., Pasquale, S., et al: ‘Thermal management of a formula E electric motor: analysis and optimization’, Appl. Therm. Eng., 2019, 157, p. 113733.
    20. 20)
      • 2. Liu, X., Chen, H., Zhao, J., et al: ‘Research on the performances and parameters of interior PMSM used for electric vehicles’, IEEE Trans. Ind. Electron., 2016, 63, (6), pp. 3533–3545.
    21. 21)
      • 23. Huang, Z., Fang, J., Liu, X., et al: ‘Loss calculation and thermal analysis of rotors supported by active magnetic bearings for high-speed permanent-magnet electrical machines’, IEEE Trans. Ind. Electron., 2016, 63, (4), pp. 2027–2035.
    22. 22)
      • 6. Ma, C., Qu, L.: ‘Multi-objective optimization of switched reluctance motors based on design of experiments and particle swarm optimization’, IEEE Trans. Energy Convers., 2015, 30, (3), pp. 1144–1153.
    23. 23)
      • 22. Li, K., Wang, S., Sullivan, J.P.: ‘A novel thermal network for the maximum temperature-rise of hollow cylinder’, Appl. Therm. Eng., 2013, 52, (1), pp. 198–208.
    24. 24)
      • 10. Putra, N., Ariantara, B.: ‘Electric motor thermal management system using L-shaped flat heat pipes’, Appl. Therm. Eng., 2017, 126, pp. 1156–1163.
    25. 25)
      • 14. Chen, H., Yan, W., Gu, J., et al: ‘Multi-objective optimization design of a switched reluctance motor for low-speed electric vehicles with a taguchi–CSO algorithm’, IEEE/ASME Trans. Mechatronics, 2018, 23, (4), pp. 1762–1774.
    26. 26)
      • 20. Zhang, B., Qu, R., Wang, J., et al: ‘Thermal model of totally enclosed water-cooled permanent-magnet synchronous machines for electric vehicle application’, IEEE Trans. Ind. Appl., 2015, 51, (4), pp. 3020–3029.
    27. 27)
      • 19. López-Torres, C., Garcia, A., Riba, J., et al: ‘Computationally efficient design and optimization approach of PMa-SynRM in frequent operating torque–speed range’, IEEE Trans. Energy Convers., 2018, 33, (4), pp. 1776–1786.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-epa.2020.0136
Loading

Related content

content/journals/10.1049/iet-epa.2020.0136
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading