Adaptive prioritization of a situation-based power management for hybrid electric vehicles

Hybrid electric vehicles can provide better performance assuming the power is intelligently and adaptively managed among the multiple sources in real-time. Most of the available power management strategies are either non-optimal or are not real-time applicable. Only a few focus on multiple and conflicting challenges of optimization objectives. In this contribution a fuel cell-battery-supercapacitor EV is considered with optimized rule-based power management. An important aspect of the optimized rule-based controller concept is its ability to offer flexibility of changing the priority or weights between the objectives so as to obtain an improved battery life or a better fuel economy or a better drivability. The weights are a representative of different rule-sets which prioritize either or a combination of the objectives. A concept of adaptive prioritization is proposed which can limit/allow the usage of each of the HEV sources depending on the driver/situation requirements and assumed future priorities. The simulation results with two different drive cycles, indicate the switching between rule sets to give better results with reference to one or two objectives at the cost of the other and vice versa.