Chapter 12 - Energy management system and strategy for a fuel cell/battery hybrid power

Abstract

This chapter presents several basic architectures of power trains for unmanned aerial vehicles (UAVs) based on traditional internal combustion engines (ICEs) and fuel cells. The developing trends of renewable energy applications in UAVs are analyzed in this chapter. The necessity of energy management systems and strategies for power trains of UAVs is discussed according to the overall flight performance index of UAVs. The power flow relationship from the propulsion system to the power train is derived to propose the optimal energy management strategy (EMS) for UAVs. The review and analysis of different energy management system architectures are given to consider the traditional and renewable energy power train. The advantage and disadvantage of EMS are compared in this chapter. Finally, the applied example of fuel cell/battery UAV is presented in this chapter. The power model of main components of the power plant is presented according to the optimization objective. The time-varying fuel cell output power generation, the state of charge, and the power demand are considered as changeable state and decision variables in this chapter. The algorithm can make full use of the recursive optimization procedure for solving the governing functional equation beginning from the initial process state and terminating at its final state to reduce the influence on inaccurate power forecast on the fuel cell power system's operation. Numerical simulations demonstrate the effectiveness of the proposed approach based on dynamic programming (DP). The near-optimal decision obtained by other EMS strategies such as fuzzy logic and rule-based methods is very close to the global optimality by DP. The simulation and hard-in-loop experimental results verify the theoretic analysis. Finally, the developing trends for EMS of UAVs are summarized to emphasize the significance of this technology.