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Master Thesis Hv Battery Cell Aging Model
vor 2 Wochen
Tasks
Welcome to Daimler Trucks and Buses We always strive to advance all those who keep the world moving. Transport is the backbone of our economy and modern life. Without transport, factories would no longer be able to produce anything, supermarkets would not be able to sell products and travel would be unimaginable for people.
Developments such as digitalisation, autonomous driving and e-mobility represent a fundamental transformation of the transport sector, which is constantly presenting new challenges. To ensure a successful future, we rely on close and trusting cooperation - both with our customers and with our globally active team of highly competent and motivated employees.
Would you like to experience the fascination of our industry as part of our team and actively contribute to the success of Daimler Trucks and Buses?
Introduction
Scope of Work
- Introduction:
- Provide a comprehensive overview of the current state of empirical models for battery cell aging
- Literature Research:
- Conduct an exhaustive review of existing literature on battery cell aging mechanisms
- Analyze studies focusing on lithium-ion battery aging, with an emphasis on long-haul trucking environments
- Summarize findings on the impact of factors such as temperature, charge rates, and state of health (SoH) on battery aging
- Model Development:
- Develop an improved empirical model for predicting battery cell aging
- Incorporate factors identified in the literature review, such as lithium deposition, anode material loss, and temperature variations
- Validate the model using experimental data from commercial and lab-made cells
- Data Analysis:
- Collect and analyze data on battery performance under various conditions
- Identify trends and patterns that influence the aging process, particularly the crossover temperature between dominant aging mechanisms
- Optimization and Validation:
- Optimize model parameters to improve accuracy and reliability
- Validate the improved model against real-world data from long-haul truck batteries
- Provide recommendations for optimal operating conditions and battery management strategies
- Reporting and Documentation:
- Document all findings, methodologies, and model development processes
- Prepare a comprehensive thesis report, including detailed analysis, results, and recommendations
- Present findings to the R&D team
The final thesis selection is made in close consultation with you, the university and the hiring department.**Qualifications**:
Our company culture
- Job number:
- DAI000187U- Publication period:
- 06/19/2024 - 07/17/2024- Location:
- Stuttgart- Organization:
- Daimler Truck AG- Job Category:
- Others- Working hours:
- Full time- To Location: Stuttgart - Untertürkheim, Daimler Truck AGContact
- Katharina Monfort
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