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Automobile tire pressure and temperature forecast base on grey model

机译:基于灰色模型的汽车轮胎气压温度预测

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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.
机译:汽车轮胎爆裂引起的交通事故给社会带来了巨大的损失,因此轮胎爆裂的预防研究是汽车电子技术中最重要的课题之一。许多设备使用轮胎内部的压力和温度数据作为主要数据源,以监视轮胎状况并提供预警。但是没有考虑轮胎压力和温度的机制,因此常用的方法不能精确预测爆破点的压力和温度。科学上没有足够的压力和温度数据,我们用灰色模型分析了压力和温度数据,适合于少量数据的分析。首先,我们在我们的设备的专业研究中心进行了实验,以获取轮胎内胎的压力和温度数据。其次,这些数据使用某种统计理论进行处理,例如消除总误差和插值。第三,使用灰色模型预测压力和温度值,并根据模型的准确性精心选择模型的代谢参数。具有异常数据的时间将被视为轮胎爆裂的时间,因此设备将向驾驶员发出警告。实验表明,灰色模型可以快速,准确地预测内胎的压力和温度值,是汽车轮胎爆裂预警硬件系统的理想选择。

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