Route-optimized Drive Mode Switching Control for Plug-in Hybrid Vehicles: Controller Design and Experimental Validation

This paper presents a route-optimized drive mode switching control method for plug-in hybrid vehicles (PHVs) and its experimental validation. The research objective is to reduce fuel usage in situations where energy consumption along a route is probabilistically estimated from historical driving data. To address this, this study develops a driving-route model based on road grades and vehicle speed distributions with terrain maps and driving profiles. The driving-route model allows us to predict fuel and electricity demands on the planned route by applying energy consumption maps relating to drive modes of a PHV on the market. Moreover, the driving-route model can be shared among any PHVs, even if the powertrain properties differ. These models are leading to formulate an integer linear programming problem deciding the drive modes for reducing fuel consumption. In addition, this paper introduces an experimental system to show the proposed approach is applicable to the actual PHV. The experimental validation on the PHV indicates that this method can improve fuel efficiency compared with that of a conventional method.