TR2022-087

Modeling, Simulation and Control of Turboelectric Propulsion Systems for More Electric Aircrafts using Modelica


    •  de Castro, M., Wang, Y., Vanfretti, L., Wang, H., Liu, D., Bortoff, S.A., Takegami, T., "Modeling, Simulation and Control of Turboelectric Propulsion Systems for More Electric Aircrafts using Modelica", AIAA Aviation Forum, DOI: 10.2514/​6.2022-3873, June 2022, pp. 3873.
      BibTeX TR2022-087 PDF
      • @inproceedings{deCastro2022jun,
      • author = {de Castro, Marcelo and Wang, Yebin and Vanfretti, Luigi and Wang, Hongyu and Liu, Dehong and Bortoff, Scott A. and Takegami, Tomoki},
      • title = {Modeling, Simulation and Control of Turboelectric Propulsion Systems for More Electric Aircrafts using Modelica},
      • booktitle = {AIAA Aviation Forum},
      • year = 2022,
      • pages = 3873,
      • month = jun,
      • doi = {10.2514/6.2022-3873},
      • url = {https://www.merl.com/publications/TR2022-087}
      • }
  • MERL Contacts:
  • Research Areas:

    Electric Systems, Multi-Physical Modeling, Optimization

Abstract:

As industry moves towards More Electric Aircraft technologies, electrification of non- propulsive loads is becoming more common. Moreover, new designs for electrified propulsive systems have been proposed in the literature, drawing attention from the aviation sector. Amidst the proposed topologies, turboelectric architectures present a set of benefits, becoming attractive for more electric powertrains. Given this context, this current paper presents Modelica as the means for developing models to assess the dynamic performance for the different possible turboelectric architectures that can be adopted by industry in the next few years. Individual components have their mathematical models presented along with their respective Modelica implementation. Two different possible architectures are assembled using the Modelica models and their dynamic performances over a 400-second sample flight mission are assessed. The dynamic simulations provide insights for choosing system’s parameters, controllers’ design, and system sizing.