Establishment and validation of ambient temperature prediction model vehicle platform compartments

Abstract

Purpose: The purpose of this study is to accurately predict the temperature induced by the vehicle platform in the process of driving, which can provide a more accurate input for proposing the environmental adaptability requirements of onboard equipment and carrying out environmental adaptability design and test validation. Approach: A dynamic temperature prediction algorithm of the vehicle platform based on the measured data is proposed by starting from the thermal formation mechanism of the vehicle platform compartment, taking into consideration the comprehensive influence of various factors on the thermal environment of the compartment, and introducing the position relationship, According to the established model, taking the normal driving of the vehicle as the starting point, the sinusoidal function is used to fit and regress the ambient temperature, and the nonlinear minimum function to fit the model parameters. Result:The result of model validation shows that the established dynamic temperature prediction model can accurately predict the curve of the temperature in the manned compartment of the vehicle platform that changes with the condition of the vehicle in travel. The error analysis results show that the maximum median error of the dynamic temperature model is not more than 2% in relation to the existing position of the passenger compartment of the vehicle platform.