Multi-Level Energy Management—Part II: Implementation and Validation

Abstract In hybrid electric vehicles, energy management systems (EMS) using optimization show superior fuel efficiency compared to rule-based strategies. However, little research shows its real-life applicability. In Part II of this work, the multi-level, model-predictive EMS from Part I is implemented on a heavy-duty parallel hybrid electric vehicle, using GPS and map data as preview. The power split, hybrid mode, and gear selection, including switching costs, are optimized in real time, thereby proving the feasibility of optimal control techniques for hybrid driveline control. Functional validation of the EMS on a test track confirm the fuel-saving mechanism as simulated in Part I. In addition to a fuel saving of 36%, the EMS also improves the drivability, by reducing the amount of open driveline events. View Full-Tex