the 4th IEEE Conference on Control Technology and Applications
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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 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.
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