A Predictive Energy Management Strategy for Hybrid Electric Powertrain With a Turbocharged Diesel Engine

Abstract

This paper proposes an energy management strategy for a hybrid electric vehicle (HEV) with a turbocharged diesel engine. By introducing turbocharger to the HEV powertrain, air path dynamics of engine becomes extremely complex and critical to engine torque response during transient processes. Traditional strategy that adopts steady-state-map based engine model may not work properly in this situation as a result of its incapability of accurately capturing torque response. Thus, in this paper, a physical-law based air path model is utilized to simulate turbo “lag” phenomenon and predict air charge in cylinder. Meanwhile, engine torque boundaries are obtained on the basis of predicted air charge. A receding horizon structure is then implemented in optimal supervisory controller to generate torque split strategy for the HEV. Simulations are conducted for three cases: the first one is rule-based torque-split energy management strategy without optimization; the second one is online optimal control strategy using map-based engine model; and the third one is online optimal control strategy combining air path loop model. The comparison of the results shows that the proposed third method has the best fuel economy of all and demonstrates considerable improvements of fuel saving on the other two methods.