Charge Transport and Energy Accumulation Breakdown Probability Distribution Characteristics of Polyimide

Polyimide (PI) has excellent electrical insulation properties and is widely used in pulsed power devices and new energy vehicles. It is of great significance to study the breakdown characteristics and mechanism of insulating materials to ensure the safe and reliable operation of electrical equipment. The key problem is to establish the correlation between the spatial dispersion of polyimide charge transport parameters and the breakdown probability distribution characteristics. In this paper, polarization, trap distribution, carrier mobility and breakdown Weibull distribution of polyimide were studied. Then, considering the physical processes such as charge transport, molecular chain displacement and charge energy accumulation, the breakdown probability model of space charge and energy accumulation modulation was established. The breakdown probability distribution characteristics of polyimide were calculated by simulation, which follows Weibull distribution, and the relationship between characteristic breakdown strength and sample thickness follows inverse power function. The breakdown Weibull distribution curves with different shape parameters were obtained by adjusting the dispersion of charge transport parameters. By comparing the simulation results with the experimental results, the variances of four characteristic parameters of charge transport, such as carrier mobility, attempted escape frequency, trap energy level and trap density, are obtained by inversion. The dispersion of trap levels is a key factor affecting the shape parameters of breakdown Weibull distribution. The probability distribution of the breakdown strength is caused by the difference of charge trapping effect of traps in different spatial locations. With the increase of sample thickness, the dispersion of trap energy level increases, and the Weibull distribution shape parameter decreases gradually. The correlation between the spatial dispersion of trap energy levels and the breakdown probability distribution is revealed, which provides theoretical basis and model support for the design and risk assessment of high voltage power equipment.