Volume 36: Intelligent Energy Solutions for Resilient Urban Systems

Multi-objective co-optimization of networked fuel cell hybrid vehicle considering signal light information Liang Chang, Baodi Zhang

Abstract

In urban driving scenarios, Fuel cell hybrid vehicle (FCHV) needs to face mixed driving scenarios while taking into account multiple objectives such as traffic safety, driving comfort and energy efficiency. The trade-off problem of multi-objective co-optimization is ignored for cruise control and energy management strategy (EMS), which are easily affected by the predefined driving cycle constraints. In this paper, the integrated control framework of cooperative adaptive cruise control (CACC) and EMS is established, and the chaotic multi-objective particle swarm optimization algorithm (CMOPSO) is adopted to optimize the control parameters of the integrated framework. The results show that compared with the control strategy optimized based on WLTC conditions, it can reduce the integrated energy consumption (4.1%) and the following safety (58.1%) while meeting the driving comfort requirements. Compared with the weighted sum method, the proposed method can achieve the balance of multiple optimization objectives.

Keywords fuel cell, networked vehicle, multi-objective optimization, cooperative adaptive cruise control