Preliminary design of helicon plasma thruster by means of particle swarm optimization

被引:5
|
作者
Coppola, G. [1 ]
Panelli, M. [1 ]
Battista, F. [1 ]
机构
[1] Italian Aerosp Res Ctr, CIRA, Via Maiorise, I-81043 Capua, CE, Italy
关键词
Compilation and indexing terms; Copyright 2024 Elsevier Inc;
D O I
10.1063/5.0149430
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Radio-frequency and Helicon Plasma Thrusters have emerged as viable electric propulsion systems due to their high plasma density, thrust density, and useful life. Helicon Plasma Thruster (HPT) is a very attractive technology because it could use many propellants and does not require hollow cathodes or grids, overcoming their associated critical erosion problem and extending the thruster's lifetime to some tens of thousands of hours. Despite the fact that high-power HPTs have reached 30% efficiency in laboratory configurations, sophisticated numerical models are required for a deeper understanding of the main plasma phenomena and for the preliminary design to increase the very low HPT's efficiency (3-7%) typical of the low-power class thrusters. The paper focuses on the development of a model for the low-medium power range (50-2000 W) of HPTs design. Starting from Lafleur's model, it has been improved with the hypothesis of neutral gas being expelled at the real thruster's wall operative temperature (300-600 K) in place of the more frequent laboratory temperature assumption (300 K). This hypothesis affects total thrust and specific impulse by about 10%. A parametric analysis of the slenderness ratio (chamber length-to-radius) has been conducted. The results showed that slender configurations lead to higher efficiencies. Downstream from the numerical model validation, a tool for the global design has been built with the Particle Swarm Optimization (PSO) technique that leads to optimal thruster configuration. This tool has been used to design a 4 mN HPT tuning the PSO in order to minimize the dimensions and the weight according to the assigned mission constraints (i.e., power, thrust, and weight). A total efficiency of 10.4% results. (c) 2023 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
引用
收藏
页数:15
相关论文
共 50 条
  • [1] Optimization of Antenna-Plasma Interaction in a Helicon Plasma Thruster
    Melazzi, D.
    Lancellotti, V.
    De Carlo, P.
    Manente, M.
    Pavarin, D.
    2014 8TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP), 2014, : 1320 - 1323
  • [2] Progress on the research of helicon plasma thruster
    Xia, Guang-Qing
    Wang, Dong-Xue
    Xue, Wei-Hua
    Zhang, Jia-Liang
    Tuijin Jishu/Journal of Propulsion Technology, 2011, 32 (06): : 857 - 863
  • [3] Helicon plasma thruster discharge model
    Lafleur, T.
    PHYSICS OF PLASMAS, 2014, 21 (04)
  • [4] Numerical Model of a Helicon Plasma Thruster
    Magarotto, Mirko
    Manente, Marco
    Trezzolani, Fabio
    Pavarin, Daniele
    IEEE TRANSACTIONS ON PLASMA SCIENCE, 2020, 48 (04) : 835 - 844
  • [5] Design Optimization of a Helical Plasma Thruster
    Beklemishev, Alexei D.
    OPEN MAGNETIC SYSTEMS FOR PLASMA CONFINEMENT (OS2016), 2016, 1771
  • [6] Design of Microstrip-Like Interconnect Lines by Means of Particle Swarm Optimization
    Yilmaz, Asim Egemen
    PRZEGLAD ELEKTROTECHNICZNY, 2010, 86 (02): : 30 - 33
  • [7] Analysis of a cusped helicon plasma thruster discharge
    Jimenez, Pedro
    Zhou, Jiewei
    Navarro, Jaume
    Fajardo, Pablo
    Merino, Mario
    Ahedo, Eduardo
    PLASMA SOURCES SCIENCE & TECHNOLOGY, 2023, 32 (10):
  • [8] Development of a Plasma Chemistry Model for Helicon Plasma Thruster analysis
    Enrico Majorana
    Nabil Souhair
    Fabrizio Ponti
    Mirko Magarotto
    Aerotecnica Missili & Spazio, 2021, 100 (3): : 225 - 238
  • [9] Solution of Orifice Hollow Cathode Plasma Model Equations by Means of Particle Swarm Optimization
    Coppola, Giovanni
    Panelli, Mario
    Battista, Francesco
    APPLIED SCIENCES-BASEL, 2024, 14 (13):
  • [10] Preliminary Study on the Particle Swarm Optimization with the Particle Performance Evaluation
    Pluhacek, Michal
    Senkerik, Roman
    Zelinka, Ivan
    ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING ICAISC 2014, PT I, 2014, 8467 : 395 - 405