Altitude Prediction Using Real Time GPS Data in HIGHWAY with GRADIENT

Abstract

In automatic cruise mode, gradient resistance is an important variable among road loads. The gradient resistance which is dependent on the slope of a road has a significant impact on fuel efficiency. Altitude data, variables of the gradient resistance, can be obtained from the GPS data which have been received on a realtime basis. Therefore, it is possible to calculate velocity using the gradient resistance which has been obtained from the altitude data in the past and present. Unless these altitude data are available, it is difficult to predict velocity. In this study, altitude data are predicted on a realtime basis, using the autoregressive (AR) algorithm. In addition, Autoregressive with Moving Window (ARMW) which has been improved based on the realtime altitude prediction and ARMWc algorithm in which velocity bas been compansated in consideration of actual altitude are proposed in this study. Using each prediction algorithm, furthermore, fuel economy in cruise mode has been evaluated in steep Yeongdong Highway. As a result, the altitudes predicted based on the altitude prediction algorithm properly follow actual altitudes. Fuel economy was higher by 4.35% compared to the cruise mode (100km/h) when CVELCONT3 cruise control algorithm was applied to the road in ARMWc(p=3) prediction altitude. In addition, the fuel economy was 98.94% compared to CVELCONT3 cruise control algorithm on the actual altitude road.KeywordsAutoregressionPredictionFuel EconomyVelocity ProfileGrade