Performance Analysis And Structure Optimization Of Hybrid Excitation Claw Pole Generator

Because of increasing automobile electric equipment, while leaving the generator space is limited, so people began to seek the premise of constant volume how to improve the output power of the generator. Therefore, the hybrid excitation claw-pole generator has become a focus of research. Based on Ansoft Maxwell3D electromagnetic simulation software to analyze and research the structure and performance of hybrid excitation claw-pole generator. The main work of this paper is as follows:The use of hybrid excitation structure both to improve low speed output capability, while the magnetic flux leakage can be reduced to improve the efficiency of the motor. Five different structures of hybrid excitation claw-pole generator for finite element modeling and simulation, comparison of these five kinds of hybrid excitation structure of the output capability, harmonic, voltage waveform. The output capability of tangential hybrid excitation structure is the largest, with good performance.By the finite element method to analyze leakage magnetic, air gap magnetic field, inductance, iron loss of the hybrid excitation claw pole generator. To explore the distribution of motor magnetic flux leakage, the main harmonic components of the air-gap flux density, magnetic saturation effect on the inductance, stator and rotor iron loss and the electromagnetic force and motor noise order relations.By the finite element method to analyze the length of air gap, pole arc coefficient, the height of stator, stator winding and excitation winding wire diameter and the number of turns, study the effects of these parameters on the generator output performance, for the design of hybrid excitation claw machine generator selection of these parameters to provide a certain reference value.Based on Support Vector Machine non-parametric modeling ideas, create a non-parametric model of hybrid excitation claw-pole generator, then using particle swarm optimization (PSO), chaos optimization algorithm (Chaos) and chaotic particle swarm optimization (CPSO) for hybrid excitation claw machine generator structure parameter optimization, to arrive at the optimal structural parameters hybrid excitation claw-pole generator.