Avionics System Design using MBSE Methodology

Abstract

The West Air Sweden Flight 294 serves as a reminder of tragic crashes of aircraft due to Avionics System failure. Due to malfunction of the Inertial Reference Unit (IRU), the aircraft lost its control resulting in tragic loss of life of the people on board. The Avionics System is a complex set of instruments, logical and physical links which must comply with the guidelines of Dob178c. The design of the system is complicated. This paper aims to understand the behavior of the Avionics System using the state-of-the-art Model Based System Engineering (MBSE) technology. This includes the two widely used tools – Capella and Simulink. We aim to understand the dynamic nature of avionics through these tools. Model Based System Engineering can be specifically beneficial because it will help the engineers to detect the flaws in the avionics system much earlier. This will potentially contribute to helping to prevent aircraft crashes due to avionics system failure. The idea of model-based system engineering includes the concept of taking a model as a reference to systematically solve the complex designs of any engineering stage. Before the concept of Model Based Systems Engineering came to be, Documents Based Systems Engineering was the trend in the system engineering department. However, it would take a lot of time, effort and accuracy to correctly pinpoint the information and accordingly design the system from a bunch of documents. MBSE, however, eases such kind of trouble by providing a model as a reference for the systems design.

Introduction

I. INTRODUCTION

Avionics system is a complex set of logical and physical links connected to different instruments displaying information on the screen for the pilot. This information is transmitted and processed through the navigation computer. Document Based System Engineering (DBSE) was introduced as method to aid in design of a product by utilizing documents and their written data. It majorly relies on the paperwork and management of the written data. However System Engineering is more complex than meets the eye. It is an interconnected and an iterative process of design between 3 different parties:

• Stake Holders: start the project, customers, assign the value to the product.
• Project Management: scheduling, budget
• Engineering Specialists: core, domain, knowledge

A, B,C – The whole process is guided by Systems Engineering.

What is System Engineering?

It is a concept and a method of designing complex entities which cannot be designed as a single entity.

Example?

Supposedly there is an idea to make a drone. System Engineering helps to guide the engineering process and ensure that the project needs are being met.

Breaking down system engineering’s function systematically: Project Objectives -> Different ideas to achieve this project Let these ideas be:

• *
• !
• .
• ,                         ,

We select one of these after narrowing down the options through analysis. In our case * is selected.

However, * is complex and big.

The obvious approach is to break down “*” into smaller and simpler components which can be easily designed and engineered. Lets say these smaller sub components are:

• |
• \
• /
• -

System Engineering will ensure each component above will do what its supposed to do. Then the proceeding integration of the components must perform the function. This will theoretically lead to the formation of a proper product. However, in reality, the process involves coordination between all three stakeholders, project management and the engineers in their own respective ways.

As we study this report, chapter 2 will talk about the Model Based System Engineering Technology and how the avionics system works. Chapter 3 will talk about the software Capella and its different analysis layers. We will study about the proposed work in capella and how this capella model can be further simulated using MATLAB. Chapter 5 will discuss the overall results and finally chapter 6 will cite references which inspired this work and report.

References

[1] Barthélémy Attanasio, Délia Cellarier, Regis De Ferluc. MODEL- BASED SYSTEM ENGINEERING FOR AVIONICS PROCESSES- 2017 [2] D. Perillo, C. S. Malavenda. Adoption of model based solution for MBSE transition , MBSE-2020 workshop [3] Régis De Ferluc, Marco Panunzio. Experience Report: History and State of the Practice of Model-Based Software Engineering in Thales Alenia Space in France, MBSE-2020 workshop [4] P Roques. MBSE and ARCADIA method. 2016 European Congress on Embedded Time [5] U Sukhatme, JTT Van, Cl Tan. Dual Parton Model. 1994 – Elsevier [6] Y Chen. Simulation Technique with MATLAB. 2013 [7] LA Dessaint, K AI-Haddad. Simulation tool based on Simulink. 1999 – IEEE Transactions [8] H Klee, R Allen. Simulation of Dynamic System. 2018 – taylorfrancis [9] BS Blanchard. System Engineering Management. 2004 [10] K Forsberg, H Mooz. Relationship of System Engineering with project cycle. 1991.

Copyright

Copyright © 2024 Aryan Rahaman, Abhinav Sharma. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.