Real Coded Genetic Algorithm for Jiles–Atherton Model Parameters Identification

Leite, Jean V.; Avila, Sergio; Batistela, Nelson Jhoe; Carpes, W.P.; Sadowski, N.; Kuo‐Peng, Patrick; Bastos, J.P.A.

doi:10.1109/tmag.2004.825319

Cited by 91 publications

(49 citation statements)

References 10 publications

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“…However, when applying the model, five key parameters need be determined by fitting based on test data with a complex mathematical method. Leite et al [34] used a genetic algorithm to determine the five parameters and verified them using the least mean square error between the experimental and simulated results. Jaafar [35] studied the influence of the five parameters on the magnetization process and found that each parameter significantly impacts the prediction accuracy of the magnetization and hysteresis mathematical models.…”

Section: -Magnetization Curvementioning

confidence: 99%

Investigation on Electromagnetic Models of High‐Speed Solenoid Valve for Common Rail Injector

Zhao

Fan

Liu

et al. 2017

Mathematical Problems in Engineering

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A novel formula easily applied with high precision is proposed in this paper to fit the -curve of soft magnetic materials, and it is validated by comparison with predicted and experimental results. It can accurately describe the nonlinear magnetization process and magnetic saturation characteristics of soft magnetic materials. Based on the electromagnetic transient coupling principle, an electromagnetic mathematical model of a high-speed solenoid valve (HSV) is developed in Fortran language that takes the saturation phenomena of the electromagnetic force into consideration. The accuracy of the model is validated by the comparison of the simulated and experimental static electromagnetic forces. Through experiment, it is concluded that the increase of the drive current is conducive to improving the electromagnetic energy conversion efficiency of the HSV at a low drive current, but it has little effect at a high drive current. Through simulation, it is discovered that the electromagnetic energy conversion characteristics of the HSV are affected by the drive current and the total reluctance, consisting of the gap reluctance and the reluctance of the iron core and armature soft magnetic materials. These two influence factors, within the scope of the different drive currents, have different contribution rates to the electromagnetic energy conversion efficiency.

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Section: -Magnetization Curvementioning

confidence: 99%

Investigation on Electromagnetic Models of High‐Speed Solenoid Valve for Common Rail Injector

Zhao

Fan

Liu

et al. 2017

Mathematical Problems in Engineering

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“…The optimal values of seven parameters and are estimated using the DE algorithm. Past studies have presented a number of optimal algorithms, such as the genetic algorithm (GA) [10], [11]; neural networks [12]; particle swarm optimization (PSO) [13] , etc. However, in cases of transformer internal fault identification, GA often has difficulties finding the global minimum due to premature convergence [10] and, moreover, iteration and calculation time of GA are more than DE.…”

Section: Optimization Methodsmentioning

confidence: 99%

Distinguishing Internal Winding Faults From Inrush Currents in Power Transformers Using Jiles-Atherton Model Parameters Based on Correlation Coefficient

Huang

Chen

et al. 2012

IEEE Trans. Power Delivery

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This study proposes a novel method using Jiles-Atherton model parameters to identify small fault current results from winding turn-to-turn short circuit in power transformer inrush current. The waveform symmetry and hysteresis curve shapes of inrush current with fault current are different from inrush current without fault current; that means the magnetic parameters of transformer cores and windings are influenced. Moreover, cycle leakage inductance and cycle winding resistance also can be used to distinguish inrush current and internal fault current due to changes of permeability and the winding current density caused by transformer core or winding state changes. Jiles-Atherton parameters per cycle, leakage inductance per cycle, and the winding resistance per cycle are estimated from the exciting inrush current per cycle under no-load conditions using the differential evolution algorithm. This study uses two types of parameters: the first is the correlation coefficient of Jiles-Atherton parameters of a transformer under no-load exciting condition. The second type is the variation trend of the cycle leakage inductance and the cycle winding resistance. The study uses cross validation of the two methods to distinguish whether inrush current contains small fault current. The experiment has verified the feasibility and accuracy of the proposed methods in this study.

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“…Nowadays GA is considered a bit of an outdated technique (originally proposed by Holland in 1975), in most cases it has been successfully superseded by the more recent and effective differential evolution. Genetic algorithms, either in the binary or floating number representation, have been successfully applied for the task of recovery of optimal values of JA model parameters in the papers [1,[15][16][17][18][19].…”

Section: Comparison Of Different Estimation Techniquesmentioning

confidence: 99%

A Comparison of Different Estimation Methods for Hysteresis Modelling

et al. 2017

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The paper focuses on the estimation techniques for a low-dimensional phenomenological model of ferromagnetic hysteresis proposed by the Brazilian research group GRUCAD. The description is expressed with an ordinary differential equation and some auxiliary relationships. It describes both irreversible and reversible magnetization processes and addresses some problems inherent in the well-known Jiles-Atherton model. It is found that the differential evolution method is the most competitive technique for recovery of optimal model parameters.

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Real Coded Genetic Algorithm for Jiles–Atherton Model Parameters Identification

Cited by 91 publications

References 10 publications

Investigation on Electromagnetic Models of High‐Speed Solenoid Valve for Common Rail Injector

Investigation on Electromagnetic Models of High‐Speed Solenoid Valve for Common Rail Injector

Distinguishing Internal Winding Faults From Inrush Currents in Power Transformers Using Jiles-Atherton Model Parameters Based on Correlation Coefficient

A Comparison of Different Estimation Methods for Hysteresis Modelling

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