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Energy management strategy of hybrid energy system for a multi-lobes hybrid air vehicle

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  • Meng, Junhui
  • Ma, Nuo
  • Meng, Fanmin
  • Zhang, Xiaohui
  • Liu, Li

Abstract

Due to the combination of aerodynamic and buoyant lift, a multi-lobes hybrid air vehicle (HAV) is very suitable for cargo transportation, communications and surveillance in the stratosphere. Solar cells can be used as an ideal energy source for the HAV because of its flat upper surface and sufficient solar radiation in the stratosphere. A hybrid energy system that combines solar cells, fuel cells and lithium batteries is considered to power the HAV in this paper. To better manage the various energy subsystems and achieve optimal flight performance, a power-following management strategy, which is a typical rule-based energy management strategy(EMS), is constructed for the hybrid energy system of the HAV. The EMS takes into account the high specific power of lithium batteries and the high specific energy of fuel cells to improve the endurance of HAV while ensuring the maneuverability during takeoff and landing. The simulation results show that output of each energy subsystem not only meets the power demand of the HAV, but also conforms to output characteristics of each subsystem. Furthermore, the simulation analysis is also carried out to investigate the impact of one of the energy failures on energy management and corresponding strategies are given. The results show the advantages of EMS proposed in this paper, which can provide a reference for the design of HAV.

Suggested Citation

  • Meng, Junhui & Ma, Nuo & Meng, Fanmin & Zhang, Xiaohui & Liu, Li, 2022. "Energy management strategy of hybrid energy system for a multi-lobes hybrid air vehicle," Energy, Elsevier, vol. 255(C).
    • Handle: RePEc:eee:energy:v:255:y:2022:i:c:s0360544222014426
    DOI: 10.1016/j.energy.2022.124539
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    References listed on IDEAS

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    1. Zhang, Lanchuan & Li, Jun & Wu, Yifei & Lv, Mingyun, 2019. "Analysis of attitude planning and energy balance of stratospheric airship," Energy, Elsevier, vol. 183(C), pages 1089-1103.
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    Cited by:

    1. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Gao, Chong, 2023. "Multi-stage distributionally robust optimization for hybrid energy storage in regional integrated energy system considering robustness and nonanticipativity," Energy, Elsevier, vol. 277(C).
    2. Fuwu Yan & Jinhai Wang & Changqing Du & Min Hua, 2022. "Multi-Objective Energy Management Strategy for Hybrid Electric Vehicles Based on TD3 with Non-Parametric Reward Function," Energies, MDPI, vol. 16(1), pages 1-17, December.
    3. Zhaowen Liang & Kai Liu & Jinjin Huang & Enfei Zhou & Chao Wang & Hui Wang & Qiong Huang & Zhenpo Wang, 2022. "Powertrain Design and Energy Management Strategy Optimization for a Fuel Cell Electric Intercity Coach in an Extremely Cold Mountain Area," Sustainability, MDPI, vol. 14(18), pages 1-16, September.

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