  This paper develops energy management (EM) control for series hybrid electric
vehicles (HEVs) that include an engine start-stop system (SSS). The objective
of the control is to optimally split the energy between the sources of the
powertrain and achieve fuel consumption minimization. In contrast to existing
works, a fuel penalty is used to characterize more realistically SSS engine
restarts, to enable more realistic design and testing of control algorithms.
The paper first derives two important analytic results: a) analytic EM optimal
solutions of fundamental and commonly used series HEV frameworks, and b) proof
of optimality of charge sustaining operation in series HEVs. It then proposes a
novel heuristic control strategy, the hysteresis power threshold strategy
(HPTS), by amalgamating simple and effective control rules extracted from the
suite of derived analytic EM optimal solutions. The decision parameters of the
control strategy are small in number and freely tunable. The overall control
performance can be fully optimized for different HEV parameters and driving
cycles by a systematic tuning process, while also targeting charge sustaining
operation. The performance of HPTS is evaluated and benchmarked against
existing methodologies, including dynamic programming (DP) and a recently
proposed state-of-the-art heuristic strategy. The results show the
effectiveness and robustness of the HPTS and also indicate its potential to be
used as the benchmark strategy for high fidelity HEV models, where DP is no
longer applicable due to computational complexity.
