Master Thesis for dynamic surrogate model development for a physics-based fuel cell system model using SINDy (dfm)

Job Description :

In order to support the Fuel Cell Systems Team within the ZEROe project Airbus Operations is looking for a

Master Thesis student for dynamic surrogate model development for a physics-based fuel cell system model using SINDy (d / f / m)

You are looking for a master thesis in a research and development environment and want to work on Fuel Cell Systems and Modeling / Simulation Then apply now! We look forward to you supporting us in the Fuel Cell Systems team as a Masters student (d / f / m)!

Location : Hamburg

Start : as soon as possible

Duration : 6 months

Proton Exchange Membrane (PEM) fuel cells enable an efficient and locally emission free conversion from hydrogen to electrical energy. This is why they are considered as important technologies to tackle the necessary mobility transition towards a sustainable aviation industry.

In the systems development approach physics-based models are capable to depict technical systems for a wide range of operating conditions. But they are too computationally demanding for certain applications (e.g. controls development) and can be challenging to cross-integrate between different tools. It is possible to build surrogate models to tackle these shortcomings. SINDy is one method that appears to be powerful in identifying the characteristic equations describing such a system as it has already given promising results on fuel cell stack / component level.

The main challenges compared to the component level will be the use of non-continuous controls inputs (e.g. valve open or closed) instead of continuous physical inputs (e.g. pressure) and a more challenging data generation. Additionally the scope of depiction is larger.

Thus SINDy shall be applied to a detailed physics-based fuel cell system model. Time series data needs to be generated in a sensible way to capture at least most of the relevant characteristics of the depicted component. From this data a surrogate model shall be built using SINDy. This model shall be evaluated with regards to computational performance prediction accuracy and its capability to extrapolate. Possible ways to re-integrate the surrogate model into the platform of the original reference model shall be examined. Optionally qualitatively different transient cases like the dynamics of a start-up or shut-down could be evaluated.

Your location

You will be working at one of the largest production sites for civil aircraft situated in Hamburg Germany. Its location on the southern banks of the river Elbe includes the option to commute by ferry. Experience the special flair of Hamburg in your spare time where vibrant cosmopolitan culture meets nautic legacy.

Your benefits

Work-life balance with a 35-hour week (flexitime).

Mobile working after agreement with the department.

Traveling within Germany (team events) is possible after consultation and agreement from the department.

International environment with the opportunity to network globally.

Work with modern / diversified technologies.

At Airbus we see you as a valuable team member and you are not hired to brew coffee instead you are in close contact with the interfaces and are part of our weekly team meetings.

Opportunity to participate in the Generation Airbus Community to expand your own network.

Your tasks and responsibilities

Literature review on time series prediction using SINDy and a fuel cell systems main characteristics and dynamics

Data generation using the physics based model including the identification of the necessary inputs outputs and transient excitements to extract models behavioral characteristics

Further development and adaptation of an existing Python framework to :

read and process multivariate time series data

generate SINDy models

handle controls inputs in addition to continuous physical inputs

evaluate model performance

Integration of the surrogate model into target platform (Dymola)

Evaluation of the surrogate models capabilities with regards to

Computational performance

Prediction accuracy

Extrapolation (with regards to input values and input dynamics)

Optional : Start-up & shut-down capabilities using a SINDy-based model

Discussion of the observed results

Desired skills and qualifications

Enrolled full-time student (d / f / m) in the area of Electrical Engineering Mechanical Engineering Chemistry Renewable Energy Systems or an equivalent field of study.

Advanced experience in the field of modeling and simulation of systems or components. A first contact with fuel cell systems or fuel cell stacks or hydrogen systems is desirable but not necessary.

Fluent in English German language knowledge is a plus.

Good knowledge of thermo-dynamics electrical power systems or electro-chemical processes.

Please upload the following documents : cover letter CV relevant transcripts enrollment certificate.

Not a 100% match No worries. Its worth it to apply anyway!

Take your career to a new level and apply online now!

This job requires an awareness of any potential compliance risks and a commitment to act with integrity as the foundation for the Companys success reputation and sustainable growth.

Company :

Airbus Operations GmbH

Employment Type : Final-year Thesis

Experience Level : Student

Job Family :

By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus.

Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background age gender disability sexual orientation or religious belief.

Airbus is and always has been committed to equal opportunities for all. As such we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to .

At Airbus we support you to work connect and collaborate more easily and flexibly. Wherever possible we foster flexible working arrangements to stimulate innovative thinking.

Key Skills

Python,C / C++,Fortran,R,Data Mining,Matlab,Data Modeling,Laboratory Techniques,MongoDB,SAS,Systems Analysis,Dancing

Experience : years

Vacancy : 1