Design and evaluation of energy management using map-based ECMS for the PHEV benchmark
Plug-in hybrid electric vehicles (PHEV) provide a promising way of achieving the benefits
of the electric vehicle without being limited by the electric range, but they increase the importance
of the supervisory control to fully utilize the potential of the powertrain. The winning contribution in
the PHEV Benchmark organized by IFP Energies nouvelles is described and evaluated. The control
is an adaptive strategy based on a map-based Equivalent Consumption Minimization Strategy (ECMS)
approach, developed and implemented in the simulator provided for the PHEV Benchmark. The implemented
control strives to be as blended as possible, whilst still ensuring that all electric energy is used
in the driving mission. The controller is adaptive to reduce the importance of correct initial values,
but since the initial values a ect the consumption, a method is developed to estimate the optimal initial
value for the controller based on driving cycle information. This works well for most driving cycles with
promising consumption results. The controller performs well in the benchmark; however, the driving
cycles used show potential for improvement. A robustness built into the controller a ects the consumption
more than necessary, and in the case of altitude variations the control does not make use of all the
energy available. The control is therefore extended to also make use of topography information that
could be provided by a GPS which shows a potential further decrease in fuel consumption.
Martin Sivertsson and Lars Eriksson
Oil & Gas Science and Technology - Rev. IFP,
2015
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