胡春明,闫丁洋,刘娜,等.油电混合动力无人机能量管理策略的对比仿真研究[J].内燃机工程,2022,43(4):74-83.
油电混合动力无人机能量管理策略的对比仿真研究
Comparison and Simulation Research on Energy Management Strategies of Oil–Electric Hybrid Unmanned Aerial Vehicle
DOI：10.13949/j.cnki.nrjgc.2022.04.009
关键词:混合动力  无人机  能量管理  动态规划
Key Words:hybrid power  unmanned aerial vehicle  energy management  dynamic programming
基金项目:国家自然科学基金面上项目（51476112）
作者单位E-mail
胡春明* 天津大学 内燃机研究所，天津 300192
天津大学 机械工程学院，天津 300072 		cmhu@tju.edu.cn 
闫丁洋 天津大学 机械工程学院，天津 300072  
刘娜 天津大学 内燃机研究所，天津 300192  
宋玺娟 天津大学 内燃机研究所，天津 300192  
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摘要:针对固定飞行任务的油电混合动力无人机，降低混合动力系统瞬时燃油消耗率，增加续航里程的工作需求，设计了可以应用于固定飞行任务油电混合动力无人机的不同能量管理策略，主要包括固定规则、模糊逻辑和动态规划算法的能量管理策略。根据油电混合动力无人机动力源特性，通过理论和试验建模相结合的方法，在MATLAB中建立油电混合动力系统的数学模型、飞行任务相对应的仿真工况及不同能量管理策略的控制程序。重点对比了基于优化的动态规划算法能量管理策略相比固定规则和模糊逻辑策略在燃油经济性和运行稳定性方面的表现。仿真结果表明：动态规划算法策略的累积燃油消耗量相比固定规则、模糊逻辑策略分别下降了4.6%和6.5%，平均瞬时燃油消耗率分别下降了5.1%和5.9%；在应对外部突风扰动时，动态规划能量管理策略的航空发动机最大转速波动相比固定规则的能量管理策略下降了59.7%，应对随机紊流扰动时，动态规划策略航空发动机的最大转速波动相比固定规则和模糊逻辑分别下降了33.9%、25.6%。动态算法作为一种全局最优算法，应用在固定飞行任务的油电混合动力无人机能量管理策略中时，可在提高混合动力系统燃油经济性的同时保证系统运行的稳定性。
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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