Optimizing Fast Charging Algorithms for Enhanced Battery Lifespan
vor 1 Monat
Our team at AVL List GmbH is seeking a highly motivated and skilled individual to assist in the development of predictive fast charging algorithms aimed at improving battery lifetime. As part of this role, you will be responsible for conducting a literature review of ageing models and existing predictive fast charging algorithms.
Responsibilities:- Literature Review and Analysis
- Algorithm Development: Design and implement a lifetime prediction model/ageing model for battery packs
- Strategy Optimization: Develop a strategy to optimize fast charging current based on actual battery pack state of health (SOH)
- Model Validation: Validate the developed model using real test data
To excel in this position, you should have ongoing bachelor studies in Electrical Engineering/Electronics, Automotive Engineering, Automation Technology, Telematics, Innovation Management or similar fields. Additionally, you should possess good knowledge in control engineering and hands-on experience with Matlab/Simulink/Targetlink.
- Ongoing Studies in Relevant Fields
- Proficiency in Control Engineering
- Matlab/Simulink/Targetlink Experience
- Excellent English Language Skills
- Possibility of Presence at Headquarters in Graz
- Independent Thesis Work with Professional Guidance and Support
- Collaboration Opportunities with Experts in the Field
- Practical Application of Theoretical Knowledge in a Real-World Environment
The successful completion of the thesis will be remunerated with a one-time fee, inclusive of taxes. Estimated annual salary in Austria is approximately €35,000 - €45,000 depending on qualifications and location.
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