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    • Comparison and Simulation Research on Energy Management Strategies of Oil–Electric Hybrid Unmanned Aerial Vehicle
    DOI：10.13949/j.cnki.nrjgc.2022.04.009
    Key Words:hybrid power  unmanned aerial vehicle  energy management  dynamic programming
    Author NameAffiliationE-mail
    HU Chunming* Internal Combustion Engine Research Institute， Tianjin University， Tianjin 300192， China
    School of Mechanical Engineering， Tianjin University， Tianjin 300072，China     		cmhu@tju.edu.cn 
    YAN Dingyang School of Mechanical Engineering， Tianjin University， Tianjin 300072，China  
    LIU Na Internal Combustion Engine Research Institute， Tianjin University， Tianjin 300192， China  
    SONG Xijuan Internal Combustion Engine Research Institute， Tianjin University， Tianjin 300192， China  
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    Abstract:Aiming at the working requirements of fixed mission oil electric hybrid unmanned aerial vehicle（UAV） to reduce the instantaneous fuel consumption rate of hybrid system and increase the endurance mileage， different energy management strategies that can be applied to fixed mission oil–electric hybrid UAV were designed. The energy management strategies mainly include fixed rules， fuzzy logic and dynamic programming. According to the power source characteristics of the hybrid UAV， through the combination of theoretical and experimental modeling methods， the mathematical model of the hybrid system， the simulation conditions corresponding to the flight mission and the control programs of different energy management strategies were established by MATLAB. The fuel economy and operation stability performance of energy management strategy based on optimization dynamic programming algorithm was compared with those of fixed rules and fuzzy logic energy management strategy. The simulation results show that the cumulative fuel consumption of dynamic programming energy management strategy reduced by 4.6% and 6.5% respectively compared with fixed rule and fuzzy logic energy management strategy，and the average instantaneous fuel consumption rate decreased by 5.1% and 5.9% respectively compared with fixed rule and fuzzy logic energy management strategy. When dealing with external gust disturbance， the maximum speed fluctuation of aero-engine with dynamic programming energy management strategy is 59.7% lower than that with fixed rules. When dealing with random turbulence， the maximum speed fluctuation of aero-engine with dynamic programming energy management strategy is 33.9% and 25.6%， respectively， than that with fixed rules and fuzzy logic energy management strategy. As a global optimal algorithm， dynamic programming algorithm is applied to the energy management strategy of oil–electric hybrid UAV in fixed mission. It can optimize the fuel economy of hybrid power system， and ensure the operation stability of the system at the same time.
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