The department of Powertrain Integration & Analytics within the Truck Technology Group at Daimler Truck AG is dedicated to developing and optimizing powertrain systems for heavy-duty commercial vehicles. Our purpose is to design high-performance, efficient, and sustainable drivetrain solutions that align with ongoing technological advancements and energy transformations, that precisely meet the requirements of our customers.
Our responsibilities include concepting innovative drivetrain architectures, defining comprehensive system requirements, and seamlessly integrating powertrain components into the overall vehicle architecture. Using data-driven analytical methods, we identify optimization potential within powertrain systems and facilitating data-based development decisions.
Through close collaboration with interdisciplinary development teams, the sales organization, and our customers, we ensure our powertrain systems meet the highest standards of performance, efficiency, and customer satisfaction.
Thesis Topic
The connectivity of commercial vehicles generates extensive volumes of telematics data, offering valuable insights into vehicle usage profiles and operational conditions. Analysis of this data enables the identification of optimization strategies within the powertrain, supporting well-founded recommendations for vehicle development and enhancing sales processes.
What We Offer:
- A dynamic and innovative work environment
- Exposure to the latest technologies and methodologies in Data Science and Analytics
- Support from an interdisciplinary and highly motivated team
The final thesis topic will be determined in collaboration with your university, yourself, and our team. If you're excited about tackling this challenge, we look forward to receiving your application.
- Data preparation and cleansing to ensure high-quality datasets for analysis
- Classification of usage scenarios based on operational and telematics data from heavy-duty trucks
- Analysis of vehicle configurations under various operating conditions
- Identification of use case profiles through AI methods to optimize vehicle configurations for performance and efficiency, and to identify appropriate use cases for zero-emission, battery-electric trucks
- Development of data-driven recommendations for development and sales teams
- Visualization and structured presentation of results for effective communication
