多旋翼混合动力无人机自适应能量管理策略仿真

Simulation of Adaptive Energy Management Strategy for Multi⁃rotor Hybrid UAVs

为提高多旋翼混合动力无人机的运行稳定性、输出动力性和能量利用率,利用GT-Power和Simulink进行模型联合搭建,对比基于规则的能量管理策略及等效燃油最小消耗能量管理策略(Equivalent consumption minimization strategy,ECMS),设计开发了基于BP(Back propagation)神经网络优化的自适应ECMS(Adaptive-ECMS,A-ECMS)。仿真研究表明:A-ECMS在运行稳定性上,整体工况转速波动率为7.74%,较基于规则策略和ECMS都有明显降低;A-ECMS在复合扰动下和随机紊流下转速波动率分别为8.32%、7.18%,与基于规则策略和ECMS相比在突发工况下运行更为稳定。A-ECMS能有效提高混合动力系统动力性能,使发动机处于经济工况10 kW;可根据荷电状态(State of charge,SOC)变化实时对电池功率进行调整。A-ECMS平均燃油消耗率为297.585 g/(kW⋅h),整体燃油消耗量为3755.31 g,与基于规则策略和ECMS相比明显较低,在各工况下运行时发动机工况点集中于燃油经济区,有效提高了系统经济性。

In order to improve the operating stability,output power and energy utilization of multi-rotor hybrid drones,GT-Power and Simulink are used to jointly build models,and rules-based consumption management strategy and equivalent consumption minimization strategy(ECMS)are compared.Adaptive-ECMS(A-ECMS)based on back propagation(BP)neural networks optimization is designed and developed.Simulation shows that in terms of operational stability of A-ECMS,the overall operating speed fluctuation rate is 7.74%,which is significantly lower than those of the rule-based strategy and ECMS.The speed fluctuation rate of A-ECMS under compound disturbance and random turbulence is 8.32%,7.18%,respectively.Compared with rule-based strategy and ECMS,it operates more stably under emergency conditions.A-ECMS can effectively improve the power performance of the hybrid system,allowing the engine to operate at an economical operating condition of 10 kW,and the battery power can be adjusted in real time according to changes in the state of charge(SOC).The average fuel consumption rate of A-ECMS is 297.585 g/(kW⋅h),and the overall fuel consumption is 3755.31 g,which is significantly lower than those of the rule-based strategy and ECMS.The engine operating points are concentrated in the fuel economy zone when running under various operating conditions.The proposed method can effectively improve system economy.