Research on energy management strategies of hybrid electric quadcopter unmanned aerial vehicles based on ideal operation line of engine

Nowadays, as concerns about pollution and energy shortages continue to mount, improvement of energy efficiency is a pressing challenge that demands urgent attention. This paper presents two energy management strategies – fuzzy logic control and model predictive control – designed for a hybrid quadrotor unmanned aerial vehicle. The strategies combine the ideal operating line of the engine and make real-time power allocation between the engine system and the battery. The ideal operating line is used to control the engine to operate at the optimal operating point for reducing fuel consumption. Additionally, this paper establishes a hybrid quadrotor unmanned aerial vehicle model and designs typical mission profiles for it. Furthermore, simulations of energy management strategies are conducted for the power demand of the typical mission. Making the result of dynamic programming as the benchmark, the results indicate that the fuzzy logic control strategy achieves 87.35 % optimal fuel consumption, and can recover and maintain a high SOC of battery, moreover, the model predictive control strategy with optimal SOC trajectory achieves 92.09 % optimal fuel consumption and can effectively maintain SOC at the target value. The strategies proposed in this paper can serve as reference methods for designing energy management strategies in hybrid quadcopter unmanned aerial vehicles.