Methodology for the Thermal Models Development of the Brazilian Inertial System

Authors

  • Fausto de Oliveira Ramos Departamento de Ciência e Tecnologia Aeroespacial – Instituto de Aeronáutica e Espaço – Divisão de Aerodinâmica, Controle e Estruturas – São José dos Campos/SP – Brazil. https://orcid.org/0009-0009-9311-1191
  • Humberto Araújo Machado Departamento de Ciência e Tecnologia Aeroespacial – Instituto de Aeronáutica e Espaço – Divisão de Aerodinâmica, Controle e Estruturas – São José dos Campos/SP – Brazil|Universidade do Estado do Rio de Janeiro – Faculdade de Tecnologia – Departamento de Mecânica e Energia – Resende/RJ – Brazil. https://orcid.org/0000-0002-1046-1770

DOI:

https://doi.org/10.1590/jatm.v18.1430

Keywords:

Thermal analysis, Inertial navigation, Hierarchical modelling, System Identification, SISNAV, MATLAB

Abstract

This work presents a methodology to produce the thermal models of the Inertial Navigation System (Sistema de Navegação Inercial), being developed along with its host micro-satellite launch vehicle by the Brazilian Air Force (Força Aérea Brasileira). The rationale is built upon (i) knowledge gathering about the modelling and identification subject and the intended use of the thermal models, (ii) selection of the model’s “box color,” (iii) determination of the theoretical and/or the experimental setup, and (iv) definition of the necessary procedures, which comprise steps, rules, and metrics for selecting and validating the models. Given the “intended use” aimed at facilitating component replacement and parameter tuning, the light-gray box approach is selected, where each component is modelled individually and subsequently grouped hierarchically as submodels. The theoretical setup utilizes the MATLAB + SIMSCAPE environment, while the experimental setup relies on the open-source electronics platform named Arduino. Finally, the procedure is defined whereby the models’ parameters are progressively tuned, based on comparisons between simulation data and experimental measurements, following the progressive aggregation of the system components. The results demonstrate a good correlation between both data and measurements across all aggregation phases. Future work includes complex scenarios and rocket launch campaign results.


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Published

2026-03-13

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Original Paper