Physics-Based Reliability Modelling of a Drone Propulsion System

Application deadline: Feb 16, 2024

This internship is open to students registered in a Bachelor's degree program. The plan is to fund this internship with the Undergraduate Student Research Award (USRA) or the Concordia Undergraduate Student Research Award (CUSRA).

The project will begin the week of April 29th, 2024. The duration is 16 consecutive weeks on a full-time basis (35 hours per week) at the High Reliability Aerospace Design Laboratory (HiRAD). The work period does not include provisions for holidays, except statutory holidays. We are looking for students not enrolled in a course during the duration of the internship.

Internship Description

The HiRAD lab specializes in advancing the design of safety-critical unmanned aerial vehicles (UAVs) by creating new methodologies and tools. Recent research has demonstrated the possibility of improving UAV reliability control through a physics- based approach [1–3]. Figure 1 illustrates the virtual and physical prototypes employed as case studies in this research.

Figure 1. HARV - Virtual (left) and Physical (right) Prototypes

The objectives of this internship are multifaceted:

1. Develop a new physics-based reliability model for UAV batteries, focusing on how battery discharge and temperature affect reliability-optimized control.

2. Investigate the impact of system redundancy on the effectiveness of the proposed reliability-optimized control approach in UAVs.

The main steps are as follows:

1. Familiarization with previous work and the concept of physics-based reliability modeling.

2. Develop a new battery physics-based reliability models in Matlab-Simulink. Validate the model with manufacturer catalog data.

3. Incorporate the newly developed reliability models into a virtual prototype, as shown in Figure 1, and validate it by simulating specific flight missions.

4. Reporting.

References

[1] Dimitri L, Liscouët J. Optimizing Flight Control of Unmanned Aerial Vehicles with Physics-Based Reliability Models. In: 2023 IEEE International Conference on Prognostics and Health Management (ICPHM). 2023, pp. 265–273.

[2] Liscouët J, Uwantare I, Remoundos A, et al. Validation of Reliability-based Flight Control Optimization for UAVs. In: AIAA SCITECH 2024 Forum. Orlando, FL: American Institute of Aeronautics and Astronautics, p. AIAA 2024-0341.

[3] Nnamdi-Nwosu I, Liscouët J. Control Allocation with Physics-Based Reliability Models for Multirotor UAVs. In: AIAA SCITECH 2023 Forum. National Harbor, MD & Online: American Institute of Aeronautics and Astronautics, p. AIAA 2023-2371.

Qualifications & Skills

• Good knowledge of aerospace and control engineering.
• Knowledge of reliability engineering is a plus.
• Experience with Matlab-Simulink.
• Interest in drone technology.
• Good writing skills.
• Professionalism.
 

How to apply

Qualified and highly motivated candidates are invited to send their application per email to jonathan.liscouet@concordia.ca using the subject " Application: Phyisics Based Reliability Modelling of UAV Propulsion Systems (USRA/CUSRA)" with the following elements:
1. Brief email with your motivation and relevant experience
2. Clarify if you candidate for either USRA or CUSRA
3. Up-to-date transcript
4. Up-to-date CV

Undergraduate Student Research Award (CUSRA)

Values of awards: $8,120 (NSERC) + $1,500 (FRQNT, competition) + $2,500 (CIADI, competition)
Prerequisite: Be a Canadian Citizen or Permanent Resident of Canada as of February 1st 2024. Be registered in a Bachelor’s degree. Have a Cumulative GPA of at least 3.00 (“B” average). 

Additional information:

• (Concordia)  https://www.concordia.ca/students/financial/scholarships-funding/awards/nserc-usra.html
• (FRQNT)  https://frq.gouv.qc.ca/en/

Concordia Undergraduate Student Resarch Award (CUSRA)

Values of awards: $8,120 (GCS) + $2,500 (CIADI, competition)

Prerequisite: Canadian, Permanent resident or International Concordia undergraduate students; Completed at least 30 credits in the program and a minimum 3.3 CGPA is required at the time of application.

Additional information:
• (CUSRA) https://www.concordia.ca/research/students-and-postdocs/undergraduate-opportunities/cusra.html