Heavy vehicles are major fuel consumers in road transportation, and the
traditional way to reduce fuel consumption is to reduce weight, resistance,
improve mechanical transmission efficiency, and improve engine thermal
efficiency. However, European heavy-duty truck companies took the lead in
realizing predictive cruise control (PCC) technology on the basis of cruise
through intelligent network technology, based on ADAS maps, and achieved good
fuel saving effects. In this paper, by studying the fuel consumption
characteristics of trucks, designing the dynamic parameters of the load and
whole vehicle, the predictive adaptive cruise control (PACC) technology is
realized based on the predictive cruise strategy, and the statistics of fuel
saving rate under different cruise ratio conditions are analyzed through the big
data platform.