Design and Evaluation of Energy Management using Map-Based ECMS for the PHEV Benchmark

Abstract

© F. Willems et al., published by IFP Energies nouvelles, 2014. 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 ofthe supervisory control to fully utilize the potential ofthe 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 ofcorrect initial values, but since the initial values affect 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 affects the consumption more than necessary, and in the case ofaltitude variations the control does not make use ofall the energy available. The control is therefore extended to also make use oftopography information that could be provided by a GPS which shows a potential further decrease in fuel consumption.