Description

At Daimler Truck we want to make a change, to create real impact together. That is why we take responsibility around the globe and work as one global team towards our vision: Leading Sustainable Transportation. It’s people who make the difference and drive success. Together, we will achieve a more sustainable transportation, reduce our carbon footprint, increase safety on and off the track, develop smarter technology and financial solutions. All essential, to fulfill our purpose for all who keep the world moving.

YOU MAKE US – YOU MAKE THE DIFFERENCE

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

We are seeking a highly motivated Master’s student to undertake a thesis project focused on improving empirical models for battery cell aging, specifically for long-haul truck applications. This research is crucial for optimizing battery management systems and extending the lifespan of batteries under various operating conditions. The selected candidate will work closely with our R&D team to develop and validate enhanced models based on extensive literature review, empirical data, and advanced analytical techniques.

Scope of Work

  • Introduction:
    • Provide a comprehensive overview of the current state of empirical models for battery cell aging
    • Identify key challenges and limitations of existing models, particularly in the context of long-haul truck applications
  • 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

  • Enrolled in a Master’s program in Electrical Engineering, Computer Schience, Mechanical Engineering, Materials Science, or a related field
  • Strong background in electrochemistry and battery technology incl. cell aging
  • Proficiency in data analysis and modeling tools (e.g., MATLAB, Python, R)
  • Experience with empirical modeling and statistical analysis
  • Excellent research and analytical skills
  • Strong written and verbal communication skills
  • Ability to work independently and collaboratively within a team

At Daimler Truck, we promote diversity and foster an inclusive corporate culture. We value the individual strengths of our employees, as these lead to the best team performance and thus to the success of our company. Inclusion and Equal opportunities are important to us – regardless of where you come from and who you are. We look forward to receiving applications from people of all cultures and genders, parents, people with disabilities and people from the LGBTIQ+ community.