### Abstract

In this paper, an optimization technique based on Genetic Algorithm (GA) is proposed to calculate the optimum phase currents of a multi-phase induction machine under phase(s) loss to maintain the same Magneto-Motive Force (MMF) distribution as with the healthy case. Conventional optimization method requires solving complex nonlinear equations. Moreover, constraints should be selected such that the number of solved equations equals the variables number to obtain a unique solution. The problem becomes complicated as the number of disconnected phases is more than two. Genetic algorithm is used to solve such optimization problem since it does not involve solving nonlinear equations. Comparison between the conventional optimization technique and GA is carried out using finite element analysis which simulates the machine flux corresponding to each optimum solution.

Original language | English |
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Title of host publication | SDEMPED 2011 - 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives |

Pages | 529-534 |

Number of pages | 6 |

DOIs | |

Publication status | Published - 2011 |

Externally published | Yes |

Event | 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2011 - Bologna, Italy Duration: 5 Sep 2011 → 8 Sep 2011 |

### Other

Other | 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2011 |
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Country | Italy |

City | Bologna |

Period | 5/9/11 → 8/9/11 |

### Fingerprint

### Keywords

- fault conditions
- finite element analysis
- genetic algorithm
- Multi-phase machine
- phase loss

### ASJC Scopus subject areas

- Energy Engineering and Power Technology
- Electrical and Electronic Engineering

### Cite this

*SDEMPED 2011 - 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives*(pp. 529-534). [6063674] https://doi.org/10.1109/DEMPED.2011.6063674

**Current optimization for an eleven-phase induction machine under fault conditions using genetic algorithm.** / Ashoush, A.; Gadoue, S. M.; Abdel-Khalik, Ayman; Mohamadein, A. L.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*SDEMPED 2011 - 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives.*, 6063674, pp. 529-534, 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2011, Bologna, Italy, 5/9/11. https://doi.org/10.1109/DEMPED.2011.6063674

}

TY - GEN

T1 - Current optimization for an eleven-phase induction machine under fault conditions using genetic algorithm

AU - Ashoush, A.

AU - Gadoue, S. M.

AU - Abdel-Khalik, Ayman

AU - Mohamadein, A. L.

PY - 2011

Y1 - 2011

N2 - In this paper, an optimization technique based on Genetic Algorithm (GA) is proposed to calculate the optimum phase currents of a multi-phase induction machine under phase(s) loss to maintain the same Magneto-Motive Force (MMF) distribution as with the healthy case. Conventional optimization method requires solving complex nonlinear equations. Moreover, constraints should be selected such that the number of solved equations equals the variables number to obtain a unique solution. The problem becomes complicated as the number of disconnected phases is more than two. Genetic algorithm is used to solve such optimization problem since it does not involve solving nonlinear equations. Comparison between the conventional optimization technique and GA is carried out using finite element analysis which simulates the machine flux corresponding to each optimum solution.

AB - In this paper, an optimization technique based on Genetic Algorithm (GA) is proposed to calculate the optimum phase currents of a multi-phase induction machine under phase(s) loss to maintain the same Magneto-Motive Force (MMF) distribution as with the healthy case. Conventional optimization method requires solving complex nonlinear equations. Moreover, constraints should be selected such that the number of solved equations equals the variables number to obtain a unique solution. The problem becomes complicated as the number of disconnected phases is more than two. Genetic algorithm is used to solve such optimization problem since it does not involve solving nonlinear equations. Comparison between the conventional optimization technique and GA is carried out using finite element analysis which simulates the machine flux corresponding to each optimum solution.

KW - fault conditions

KW - finite element analysis

KW - genetic algorithm

KW - Multi-phase machine

KW - phase loss

UR - http://www.scopus.com/inward/record.url?scp=81255176000&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=81255176000&partnerID=8YFLogxK

U2 - 10.1109/DEMPED.2011.6063674

DO - 10.1109/DEMPED.2011.6063674

M3 - Conference contribution

AN - SCOPUS:81255176000

SN - 9781424493036

SP - 529

EP - 534

BT - SDEMPED 2011 - 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives

ER -