Automobile tire pressure and temperature forecast base on grey model

Traffic accidents caused by automobile tire burst bring huge loss to the society, so the tire burst prevention research is one of the most important subjects of automotive electronic technology. Many devices use pressure and temperature data inner tire as the main data sources to monitor tire condition and provide early-warning. But the mechanisms of tire pressure and temperature weren´t considered, thus the common methods can´t precisely forecast the pressure and temperature at burst point. Science there are insufficient pressure and temperature data, we analyzed the pressure and temperature data with grey model, which is suitable for analysis of small amount of data. First, we did experiments in a professional research center with our device to acquire pressure and temperature data inner tire. Second, these data was processed with some statistic theory, such as removing the gross error and interpolation. Thirdly, the grey model was used to forecast pressure and temperature values, and the metabolic parameters of model were carefully selected according to model´s accuracy. The time with the abnormal data will be regarded as the time that tire burst, so that the device will give warnings to the driver. Experiments show that grey model can fast forecast the values of pressure and temperature inner tire with a high accuracy, which is a good choice for the automobile tires burst early-warning hardware system.