基于实车试验数据的发动机油换油周期预测模型

Drain Interval Prediction Models of Motor Oils Based on Vehicle Road Test Data

车用发动机油的不合理更换导致我国润滑油消耗量不断升高,使用成本增加,并造成环境污染等问题.本文中通过对7辆在常规城市工况条件下运行的民用轿车进行多个换油周期行车测试,定期采集润滑油样并应用PDSC方法检测试验油样的起始氧化温度,依据测试获得的312组试验数据样本,采用多重线性回归分析方法建立了润滑油起始氧化温度与车辆运行里程和运行时间之间的关系模型.结果表明:现行换油周期偏于保守,换油时的润滑油的起始氧化温度值较高,仍具有优良的氧化安定性,属于过度更换.因此,我国车用润滑油的换油周期有进一步提升的空间.数据分析发现,所建立的模型简洁直观,具有较好的拟合性以及预测精度,可供车主在决定更换润滑油时进行简单、方便和直接的判断.

The irrationality changes of motor oil has caused various problems,such as excessive consumption of lubricating oil,high maintenance costs and enduring environment pollution.Multiple road tests of 7 civilian cars were studied in this paper,which were operated under normal urban conditions.The oil samples during experimental process were regularly collected and the oxidation onset temperature(OOT)was tested by using PDSC method.The multiple linear regression method was used to establish the relationship model between the OOTs of the lubricants and vehicle parameters,including service mileage and service time based on the 312 samples.The results showed that the replaced lubricant exhibited high OOTs and still retained excellent oxidation stability,which suggested the current oil drain interval is conservative.Therefore,the level of oil drain interval in our country need to be further improved.The data analysis showed that the established models were concise with good fitting and prediction accuracy.Meanwhile,the models can be used for end users to judge the changing of lubricating oil easily and conveniently.