Predictive Energy Management Strategy for Dominant-Electric Hybrid Electric Vehicles

Abstract

Dominant-electric hybrid electric vehicles are characterized by an electrical system power that significantly exceeds the power of the internal combustion engine (ICE) and offer greater electric ranges compared to current plug-in hybrid electric vehicles. Due to the relatively small ICE, not all driving requirements can be met purely by the ICE, depending on the driving profile. Critical driving requirements can be, for example, driving at high speeds with possible additional inclines that exceed the maximum power of the ICE, or driving at low speeds where the ICE should only be operated to a limited extent due to NVH criteria. To meet the customer's performance requirements and at the same time ensure the energy stability of the hybrid system, electrical energy reserves are required in the high-voltage battery. To make the best possible use of the energy of the high-voltage battery and at the same time provide electrical energy for critical driving requirements, an energy management strategy with a predictive function based on predictive data such as route navigation is required. This paper presents a concept for the methodical development and design of a predictive energy management strategy for dominant-electric hybrid electric vehicles. Simulative studies based on an exemplary worst-case driving profile are presented and analyzed to demonstrate the functionality of the proposed energy management strategy.