Compiling vehicle durability load spectrum based on customer usage correlation
A new method to divide vehicle's driving conditions was presented and used in compiling vehicle durability load spectrum based on customer usage correlation.A seven dimension random vector was adopted to distinguish,quantify and identify road roughness,topographic feature and driving habit for division of vehicle's driving conditions.Correlation relations between the seven random variables were studied.The statistic results showed that any two variables among the seven random variables were not highly related,which indicated that further simplifying the method to divide vehicle's driving condition was not supported.Besides,the seven random variables were not independent,which highlighted the necessity to use the associated probability density distribution to describe vehicle's driving conditions.The results shown that the chosen dimensions thoroughly described and defined vehicle's driving conditions,which became an organic unity.When correlating to different loads of vehicle,the organic unity showed significant but distinctive overall correlation relationship,which could be used to compile vehicle durability load spectrum correlated to customer usage.
vehicle engineeringdriving conditionbig data analysiscustomer usage correlationvehicle durabilityload spectrum
万方数据
维普
