Practical application of natural ester insulating oils is constrained by their inherent oxidative instability

and prolonged service may lead to oxidation degradation

potentially causing oil channel blockage and insulation failure. This study systematically investigates the structure-property relationships between natural ester compositions and their pour point characteristics

while elucidating the influence patterns of various fatty acid components on oxidation induction time through molecular mechanism analysis. Building upon these fundamental insights

we developed predictive models for both oxidation resistance and pour point characteristics based on compositional parameters of natural esters

which demonstrated satisfactory predictive accuracy through validation. To achieve performance optimization

genetic algorithm was employed to conduct multi-objective component optimization of soybean oil. The ideal composition for high-performance soybean-based natural ester insulating oil was determined as C16:0:C18:0:C18:1:C18:2:C18:3= 11.08:4.08:83.50:1.34:0. This optimized formulation simultaneously enhances oxidation stability while maintaining appropriate low-temperature fluidity. The composition performance correlation model and optimization method established in this study provide theoretical guidance for the design of high-performance natural ester insulating oil.