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Working Student Electric Aircraft Propulsion Battery State Observation, Estimation and Prediction(m/w/x)
Simulating battery models with thermal and aging effects for electric aircraft propulsion. Kalman filter and state prediction algorithm development required. Flexible hours, subsidized lunch, independent projects.
Requirements
- Master's program in Electrical/Aerospace/Mechanical Engineering, Applied Mathematics, Control Engineering, or related field
- Background in control theory, state estimation, or system modeling
- Programming skills in Matlab/Simulink and optionally C/C++
- Knowledge of battery technology and battery management is a strong plus
- Experience with real-time simulation, HiL testing, or embedded systems is a plus
- Analytical mindset, attention to detail, and ability to work independently
- Ability to document technical work clearly
Tasks
- Adapt and simulate equivalent-circuit models
- Incorporate thermal, aging, and hysteresis effects
- Develop battery state estimation algorithms
- Implement and validate Kalman filters and other methods
- Create state predictors for remaining flight time
- Ensure algorithms meet ED-289 and ED-309 requirements
- Analyze data from virtual and physical test benches
- Support integration into real-time battery management software
- Document methods and validation results
- Collaborate with systems, software, and test engineers
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Matlab/Simulink
- C/C++
- Kalman filtering
- battery technology
- battery management
- real-time simulation
- HiL testing
- embedded systems
Benefits
Flexible Working
- Flexible working hours
Healthcare & Fitness
- Subsidized EGYM Wellpass membership
Free or Subsidized Food
- Subsidized lunch with 5€ company contribution
Diverse Work
- Independent projects
Team Events
- Internal social events and retreats
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Working Student Electric Aircraft Propulsion Battery State Observation, Estimation and Prediction(m/w/x)
Simulating battery models with thermal and aging effects for electric aircraft propulsion. Kalman filter and state prediction algorithm development required. Flexible hours, subsidized lunch, independent projects.
Requirements
- Master's program in Electrical/Aerospace/Mechanical Engineering, Applied Mathematics, Control Engineering, or related field
- Background in control theory, state estimation, or system modeling
- Programming skills in Matlab/Simulink and optionally C/C++
- Knowledge of battery technology and battery management is a strong plus
- Experience with real-time simulation, HiL testing, or embedded systems is a plus
- Analytical mindset, attention to detail, and ability to work independently
- Ability to document technical work clearly
Tasks
- Adapt and simulate equivalent-circuit models
- Incorporate thermal, aging, and hysteresis effects
- Develop battery state estimation algorithms
- Implement and validate Kalman filters and other methods
- Create state predictors for remaining flight time
- Ensure algorithms meet ED-289 and ED-309 requirements
- Analyze data from virtual and physical test benches
- Support integration into real-time battery management software
- Document methods and validation results
- Collaborate with systems, software, and test engineers
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Matlab/Simulink
- C/C++
- Kalman filtering
- battery technology
- battery management
- real-time simulation
- HiL testing
- embedded systems
Benefits
Flexible Working
- Flexible working hours
Healthcare & Fitness
- Subsidized EGYM Wellpass membership
Free or Subsidized Food
- Subsidized lunch with 5€ company contribution
Diverse Work
- Independent projects
Team Events
- Internal social events and retreats
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
VÆRIDION
Industry
Aerospace
Description
The company develops a full electric microliner for zero emission regional flights, aiming for certification by 2030.
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