Series hybrid electric vehicles (HEVs) employ an electric motor for propulsion,
while the internal combustion engine operates solely as a generator under
energy-efficient speed and load conditions. Owing to this architecture, series
HEVs can achieve high fuel efficiency with a relatively simple control
structure. However, conventional energy management systems (EMSs) often
prioritize battery state-of-charge (SOC) stabilization, which can lead to
frequent engine start–stop operations and unnecessary fuel consumption,
particularly in short-trip driving. This study aims to enhance energy management
performance in series HEVs by optimizing engine power generation timing based on
predicted short-trip duration. A computationally efficient, rule-based
prediction model is developed using real-world driving data, in which short-trip
duration is estimated from vehicle speed and acceleration. Due to its low
computational load, the proposed model is suitable for implementation in an
onboard electronic control unit (ECU). The proposed control strategy initiates
engine power generation when the battery SOC is low and the predicted trip
duration is long, and suppresses generation when the SOC is sufficiently high or
the predicted trip is short. A detailed vehicle model incorporating an engine,
generator, electric motor, inverter, and battery is developed in Modelica to
evaluate the proposed strategy. Simulation results demonstrate that the proposed
EMS significantly reduces the frequency of engine start–stop events, leading to
fuel economy improvements of 3.6% under the WLTC (excluding the extra-high
phase) and 13.4% in a real-world urban–rural driving cycle, compared with a
commercialized baseline vehicle. These results confirm the effectiveness and
practical applicability of the proposed EMS for passenger vehicle
applications.
