Predictive Energy Management of Range-Extended Electric Vehicles Considering Cabin Heat Demand and Acoustics

Abstract

In range-extended electric vehicles (REEV) the internal combustion engine (ICE) drives a generator in order to provide additional electric power in case of a discharged battery. As the ICE is mechanically decoupled from the wheels, it can be operated optimally in terms of emissions and acoustics. However, implementing an energy management strategy (EMS), which operates the ICE meeting the customer's demands with regard to acoustics, is a challenging task. Hence, and since the fuel economy is not very sensitive to the EMS, different works recommend easily adaptable rule based strategies. In winter scenarios the all electric range decreases drastically due to the cabin heat demand. Thus, the ICE is operated more often and an EMS utilizing the waste heat for cabin heating is promising. In this paper, the rule based strategy of the BMW i3 with range extender (RE) is rebuilt and adapted in order to exploit the available waste heat while ensuring the same acoustic comfort. In this context, a prediction model is used, which preplans the depletion of the battery with regard to the available waste heat and the demanded cabin heat. The developed EMS is evaluated in terms of savings in operating costs using a high fidelity model which is validated and calibrated with measurements on the BMW i3.