Thesis Project: 30 ECTS - Data Analysis for Drivetrain Control Optimization

Background 
Climate change mitigation is a top priority, necessitating the evaluation of all potential technological solutions to reduce greenhouse gas and other pollutant emissions in the transport sector. Scania aims to lead the way towards a more sustainable future in the transport sector. A key component of this sustainable future is battery electric vehicles (BEVs) and their continuous improvement to meet customer demands, which include high and efficient torque for driving in various conditions. 

Target 
The primary goal of this master thesis is to investigate and optimize drivetrain performance for BEVs operating under dynamic loads and varying surface conditions. By improving powertrain control strategies, the project aims to enhance vehicle efficiency, stability, and overall performance, contributing to Scania’s vision of a more sustainable and energy-efficient transport system. This research will focus on developing solutions that leverage data-driven insights to optimize torque delivery, enhance drivetrain responsiveness, and adapt vehicle behavior to changing operational conditions. 

Scope and Task 
The master thesis could focus on one, two, or all of the following areas: 

1. Load Estimation: Understanding the load from a Power Take-Off (PTO) is crucial for optimizing gear changes. We are looking for a student to develop advanced estimation techniques. 

1. Hardware protection algorithm Update: The goal is to update the HWPC algorithm based on insights gained from dynamic loads in the drivetrain.  

1. Slip Optimization for Traction: This involves developing a learning algorithm that optimizes slip for traction based on varying road surface conditions.  

What We Offer 

• Hands-on Experience: Work on real-world projects with direct applications in the automotive industry. 

• Mentorship: Collaborate with experienced professionals and researchers. 

• Innovation: Contribute to the development of advanced algorithms and techniques that will shape the future of vehicle performance. 

• Professional Growth: Gain valuable skills and knowledge that will enhance your career prospects in automotive engineering and related fields. 

• Collaborative Environment: Join a group of engineers developing software for the control and safety of electric machines. 

Requirements 

• Currently enrolled in a master's program in automotive engineering, mechanical engineering, mechatronics engineering, computer engineering, or a related field. 

• Strong analytical and problem-solving skills. 

• Experience with data analysis and algorithm development. 

• Knowledge of drivetrain systems and vehicle dynamics is a plus. 

• Ability to work independently and as part of a team. 

Contact Persons and Supervisors 

• Leo Arnholm, development engineer - leo.arnholm@scania.com 

• Vaheed Nezhadali, group manager - vaheed.nezhadali@scania.com] 

Application 
Your application must include a CV, personal letter, and transcript of grades. A background check will be conducted for this position. We are conducting interviews continuously and may close the recruitment earlier than the date specified. The project will be carried out at Scania Technical Center (STC) in Södertälje. 

A background check might be conducted for this position. We are conducting interviews continuously and may close the recruitment earlier than the date specified.