Determination of the Parameters of a DC Motor with Parallel Excitation by a Genetic Algorithm
DOI:
https://doi.org/10.48149/jciees.2024.4.1.1Keywords:
DC motor, Matlab, Genetic AlgorithmAbstract
This paper presents a method of determining the parameters of a DC motor with parallel excitation by the use of a genetic algorithm. An approach is described for determining the mutual induction coefficient, the equivalent moment of inertia of the motor armature, the coefficient of friction and the friction torque based on the transient response graphs of the armature current and the rotational frequency of the motor. The measured resistance and inductive reactance of the armature and field windings of the motor are used as input data in the optimization procedure. The determined correlation coefficient, mean deviation error and mean square error between the experimentally taken and model-derived transient response graphs of the armature current and rotational frequency of the motor confirm the applicability of the presented approach.
Metrics
References
Adewusi, S. (2016). Modeling and Parameters Identification of a DC Motor Using Constraint Optimization Technique. IOSR J. Mech. Civ. Eng. vol. 13, pp. 46–56.
Avoda, M. L. & Ramzy, S. A. (2019). Parameter Estimation of a Permanent Magnets DC motor. Iraqi J. Electr. Electr. Eng., vol. 15, pp. 28–36.
Hadef, M., Bourouina, A. & Mekideche, M. R. (2008). Parameters Identification of DC Motor via Moments Method. Iran. J. Electr. Comput. Eng. vol. 7, pp. 159–163.
Shanmuga, N. B., Mythile, A., Pavithra, S. & Nivetha, N. (2020). Parameter Identification of a DC Motor. Int. J. Sci. Technol. Rese. Vol. 9, pp. 5746–5755.
Amiri, M. S., Ibrahim & M. F., Ramli, R. (2020). Optimal parameter estimation for a DC motor using genetic algorithm. Int. J. Power Electr. Drive Syst. Vol. 11, pp. 1047–1054.
Lankarany, M. & Rezazade, A. (2007). Parameter Estimation Optimization Based on Genetic Algorithm Applied to DC Motor, In Proceeding of the International Conference on Electrical Engineering, Lahore, Pakistan, 2007, pp. 1-6, doi: 10.1109/ICEE.2007.4287313.
Jesenik, M., Hamler, A., Trbušić, M. and M. Trelep. (2000). The Use of Evolutionary Methods for the Determination of a DC Motor and Drive Parameters Based on the Current and Angular Speed Response. Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška cesta 46, 2000 Maribor, Slovenia, 2020. https://doi.org/10.3390/math8081269
Amiri, M., Ibrahim, M. & Ramli, R. (2020). Optimal parameter estimation for a DC motor using genetic algorithm. International Journal of Power Electronics and Drive Systems, Vol 11, June, pp.1047-1054, http://doi.org/10.11591/ijpeds.v11.i2.pp1047-1054.
Ruseva V., A. Krasteva. (2023). Using the Matlab Programming Environment in the Course of Student Training in the Electrical Machines Discipline. In Proceeding of the 46th MIPRO ICT and Electronics Convention (MIPRO), Opatija, Croatia, IEEE, 2023, pp. 1561-1566.
Chernykh I. V. (2008). Modelling of Electrotechnical Devices in MATLAB, SimPowerSystems and Simulink, DMK Press, Moscow.
Bebikhov Y.V., A.S. Semenov, M.N. Semenova, I.A. Yakushev. (2019). Analysis of Methods of Simulation Modelling of Technical Systems in the Matlab Environment. Modelling, Optimisation and Information Technologies. Scientific Journal, vol. 7, No. 3, 2019.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 The Journal of CIEES
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
