Optimal velocity planning and energy management for multi-objective optimization of hybrid electric vehicle

Abstract

For the past decades, researchers studied the energy management strategy of hybrid electric vehicles since it can contribute significantly to fuel consumption reduction without any change in the vehicle hardware. Unfortunately, previous studies focus on improving energy management strategy about a fixed driving cycle. To improve fuel economy further, researchers attempted to co-optimize optimal velocity planning and energy management strategy using traffic signal phasing and time information. However, since solving this co-optimization problem at once is hard to satisfy real-time control and optimality simultaneously, a new methodology to solve energy management and optimality in two parts is devised. However, even in this recent research, real-time control was lacking in the optimal velocity plan, and optimality was lacking in the energy management strategy. Thus, this thesis adds real-time control to optimal velocity planning by pre-computation of optimal fuel cell cost map and adds optimality to energy management strategy by considering road grade and SOC node update when planning SOC node and following generated SOC node by MPC. This methodology can be used for real-time control with sophisticated high performance. Further, fuel consumption reduction due to optimal velocity planning and loss of optimality reduction due to energy management strategy is analyzed by comparing proposed and compared methods. Also, fuel consumption reduction of the overall proposed method, energy balance, and loss analysis is conducted. It is expected that the proposed methodology will contribute significantly to reducing the fuel consumption of real vehicles only with software updates.