Optimal Control of Series Plug-In Hybrid Electric Vehicles Considering the Cabin Heat Demand

Abstract

In series plug-in hybrid electric vehicles, the engine is decoupled from the wheels and the fuel economy is not very sensitive to the energy management. Therefore, different works recommend charge depletion, charge sustenance (CDCS) strategies for vehicle implementation as they always ensure a desirable full exploitation of the battery capacity. In contrast, this brief illustrates great fuel saving potentials by blending CD and CS with regard to using the engine waste heat for cabin heating. In this way, the energy demand of the electric heater and thus the fuel consumption are reduced significantly. The potential is outlined by comparing the fuel consumption of optimal blended and optimal CDCS strategies for different boundary conditions. In this context, a novel hybrid optimization approach is presented, which combines dynamic programming with a genetic algorithm. Furthermore, a power to heat ratio is deduced, which is useful to interpret the results, and might support the design process of causal controllers considering the cabin heat demand.