Design and optimization of tubular linear permanent-magnet generator with performance improvement using response surface methodology and multi-objective genetic algorithm

Document Type : Article


1 Department of Electrical and Electronics Engineering, Harran University, Urfa, 63400, Turkey

2 Department of Electrical and Electronic Engineering, Faculty of Technology, Gazi University, Ankara, Turkey

3 Fatsa Faculty of Marine Sciences, Ordu University, 52400, Turkey


Linear generators are electric machines which generate electrical energy from linear movement. Since these machines can lift gear wheel or power train, they have begun to be used widely nowadays. Since their working areas differ according to speed and power characteristic, this study contains design and optimization of tubular linear generator for free piston practices. The design performed response surface optimization through design variables acquired as a result of sizing via interface. The association between the determined design variables and the sizes of generator output was examined. In addition, these sizes were used for objective functions of increasing efficiency, decreasing overall volume and increasing general performance and their optimum values were found by using Multi-Objective Genetic Algorithm. Initial and optimum design data were compared with Ansys Maxwell 2D. With overall performance increase, 22,78% decrease was seen in total mass, while 11,7% decrease was seen in cost. In addition, prototype linear generator was made in line with initial geometry data and it was applied with crank slider mechanism.


  1. References:

    1. Dalcali, A. and Akbaba, M. Optimum pole arc o_set in permanent magnet synchronous generators for obtaining lowest voltage harmonics", Scientia Iranica, Transaction D, Computer Science & Engineering, Electrical, 24(6), pp. 3223{3230 (2017).
    2. Ibtissam, B., Mourad, M., Medoued, A., et al. Multiobjective optimization design and performance evaluation of slotted Halbach PMSM using Monte Carlo method", Scientia Iranica, D, Computer Science & Engineering, Electrical, 25(3), pp. 1533{1544 (2018).
    3. Qinghua, L.I.U., Jabbar, M.A., and Khambadkone, A.M. Response surface methodology based design optimisation of interior permanent magnet synchronous motors for wide-speed operation", In Power Electronics, Machines and Drives, Second International Conference on, 2, Edinburgh, UK, pp. 546{551 (2004).
    4. Abbaszadeh, K., Alam, F.R., and Saied, S.A. Cogging torque optimization in surface-mounted permanentmagnet motors by using design of experiment", Energy Conversion and Management, 52(10), pp. 3075{3082 (2011).
    5. Jolly, L., Jabbar, M.A., and Qinghua, L. Design optimization of permanent magnet motors using response surface methodology and genetic algorithms", IEEE Transactions on Magnetics, 41(10), pp. 3928{ 3930(2005).
    6. Ghasemi, A. Cogging torque reduction and optimization in surface-mounted permanent magnet motor using magnet segmentation method", Electric Power Components and Systems, 42(12), pp. 1239{1248 (2014). 7. Yu, J.S., Cho, H.W., Choi, J.Y., et al. Optimum design of stator and rotor shape for cogging torque reduction in interior permanent magnet synchronous motors", Journal of Power Electronics, 13(4), pp. 546{ 551 (2013). 8. Bremner, R.D. Rapid optimization of interior permanent magnet (IPM) machines using the response surface method and dimensionless parameters", Graduate Theses, Iowa State University, USA (2010). 9. Jabbar, M.A., Jolly, L., and Qinghua, L. Design optimisation of permanent magnet motors using response surface analysis", In Digests 3rd International Conference on Electrical & Computer Engineering, Dhaka, Bangladesh, pp. 28{30 (2004). 10. Abbaszadeh, K., Alam, F.R., and Teshnehlab, M. Slot opening optimization of surface mounted permanent magnet motor for cogging torque reduction", Energy Conversion and Management, 55, pp. 108{115 (2012). 11. Arehpanahi, M. and Kashe_, H. Cogging torque reduction of Interior Permanent Magnet Synchronous Motor (IPMSM)", Scientia Iranica, D, Computer Science & Engineering, Electrical, 25(3), pp. 1471{1477 (2018). 12. Arslan, S., Kurt, E., Akizu, O., et al. Design optimization study of a torus type axial ux machine", Journal of Energy Systems, 2(2), pp. 43{56 (2018). 13. Saha, S., Choi, G.D., and Cho, Y.H. Optimal rotor shape design of LSPM with e_ciency and power factor improvement using response surface methodology", IEEE Transactions on Magnetics, 51(11), pp. 1{4 (2015). 14. Ahn, H.M., Chung, T.K., Oh, Y.H., et al. Optimal design of permanent magnetic actuator for permanent magnet reduction and dynamic characteristic improvement using response surface methodology", Journal of Electrical Engineering and Technology, 10(3), pp. 935{ 943 (2015). 15. Jian, L., Shi, Y., Wei, J., et al. Design optimization and analysis of a dual-permanent-magnet-excited machine using response surface methodology", Energies, 8(9), pp. 10127{10140 (2015). 16. Hasanien, H.M., Abd-Rabou, A.S., and Sakr, S.M. Design optimization of transverse ux linear motor for weight reduction and performance improvement using response surface methodology and genetic algorithms", IEEE Transactions on Energy Conversion, 25(3), pp. 598{605 (2010). 3064 S. Arslan et al./Scientia Iranica, Transactions D: Computer Science & ... 27 (2020) 3053{3065 17. Pourmoosa, A.A. and Mirsalim, M. Design optimization, prototyping, and performance evaluation of a lowspeed linear induction motor with toroidal winding", IEEE Transactions on Energy Conversion, 30(4), pp. 1546{1555 (2015). 18. Arslan, S., Gurdal, O., and Akkaya Oy, S. The design, dimensioning and optimization of a 1 Kva tubular linear alternator", International Journal of Development Research, 6(12), pp. 10550{10559 (2016). 19. Arslan S., Gurdal O., and S.A. Oy The determination of e_ects of primary and secondary geometry of tubular linear generator", IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE), 12(1), pp. 6{ 11 (2017). 20. Arslan, S., and OY, S.A. Design and optimization of tube type interior permanent magnets generator for free piston applications", TEM Journal, 6(2), pp. 214{ 221 (2017). 21. Wang, G., Chen, J., Cai, T., et al. Decompositionbased multi-objective di_erential evolution particle swarm optimization for the design of a tubular permanent magnet linear synchronous motor", Engineering Optimization, 45(9), pp. 1107{1127 (2013). 22. Amdouni, I., El Amraoui, L., Gillon, F., et al. Multiobjective approach developed for optimizing the dynamic behavior of incremental linear actuators", COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 33(3), pp. 953{964 (2014). 23. Alpar, R. Uygulamal_ _Istatistik ve Ge_cerlilik- Guvenirlik", Detay yay_nc_l_k, pp. 1{668, Ankara, Turkey (2014). 24. FAnsys-Maxwell-18-Online-Help&date=2018-07-09