Open AccessPhase-Variable Modeling and Comparative Study between a PMa-CPA and a CPA Alternator by Simulation Analysis
Author(s) -
MingFa Tsai,
ChungShi Tseng,
Shu-Yui Bai
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2179/1/012014
Subject(s) - alternator , control theory (sociology) , rotor (electric) , rectifier (neural networks) , stator , torque , engineering , voltage , power (physics) , physics , electrical engineering , computer science , stochastic neural network , control (management) , quantum mechanics , artificial intelligence , machine learning , recurrent neural network , artificial neural network , thermodynamics
This paper presents the phase-variable modeling of a permanent magnet-assisted claw-pole alternator in PSIM simulation software tool with the performance compared with a claw-pole alternator model, which is a special case of the permanent magnet-assisted claw-pole alternator model with the rotor permanent-magnet flux constant setting equal to zero. The constructed model can be simulated as a real alternator directly connected to a diode-bridge rectifier or switch-mode rectifier circuit for the integrated power application system simulation analysis. The proposed model contains two features, one of which is that the stator and rotor windings are circuit-based. The other one feature is that the mechanical torque input is based on a mathematical function. In this model, the rotor position-dependent variable inductor is replaced by a separate voltage source according to the voltage source absorption theorem. The simulation shows that the proposed model has faster torque step response and higher power efficiency than the claw-pole alternator model. The proposed model can be employed to the application of the control design and simulation study of voltage regulation in automobiles. The simulation results with 15-V command and the load sudden change verify the correction of the proposed model.