고도 및 교통정보를 활용한 예측 등가 소비 최소 전략 도출

Abstract

An optimal energy management strategy is necessary to improve fuel economy of Hybrid Electric Vehicles (HEV). Although horizon optimization strategy (e.g. Dynamic programming) guarantees global optimal solution, the strategy requires priori information about the entire optimization horizon and thus the strategy cannot be implemented in a real-time situation. Therefore, this paper proposed instantaneous optimization based Predictive Equivalent Consumption Minimization Strategy (P-ECMS) by utilizing traffic and road slope information. Battery state of charge (SOC) reference is predicted over distance. This SOC reference is adopted to supplement the limitation of ECMS, which is selection of the most suitable value of Equivalent Factor to guarantee optimality and charge sustainability for any driving conditions. As a result, the proposed PECMS achieves similar fuel economy with other instantaneous optimal control strategies like ECMS while still guaranteeing the real-time implementability.