Model Prediction and Rule Based Energy Management Strategy for Hybrid Energy Storage System

In this paper, a real-time energy management strategy is proposed for a plug-in hybrid electric vehicle with the hybrid energy storage system including a Ni-Co-Mn Li-ion battery pack and a Lithium Titanium-Oxide battery pack. Through modeling, a state-of-charge and state-of-power capability joint estimator is proposed to forecast the dynamic performance of battery packs. A model prediction and rule based energy management strategy using the joint estimator and fuzzy logic control is developed. For comparison, we analyzed a conventional rule based energy management strategy. Thereafter, a quantifiable battery degradation model and the hardware in loop tests are derived to evaluate two kinds of strategies. The results demonstrate that the overall performance of the hybrid energy storage system can be improved significantly by using the energy management strategy proposed in this paper.