Master Thesis: Data-Driven Optimization of Predictive Engine Stop/Start

Transport is at the core of modern society. Imagine using your expertise to shape sustainable transport and infrastructure solutions for the future. If you seek to make a difference on a global scale, working with next-gen technologies and the sharpest collaborative teams, then we could be a perfect match. 

Background

Predictive Engine Stop/Start (PESS) is a fuel-saving functionality for heavy-duty vehicles. By switching off the combustion engine during suitable driving conditions, PESS can reduce fuel consumption.
Our ambition is to further improve PESS by enabling the function for more customers, more vehicle applications and a wider range of operating conditions, while increasing engine-off time and maximizing fuel-saving potential.

In this thesis, you will use real-world customer vehicle data to understand how PESS performs in different operating conditions, identify what limits its utilization and investigate opportunities for further improvement.

What you will do

The thesis will include activities such as:

• Analyze customer vehicle data and PESS performance.
• Develop relevant KPIs and visualizations using tools such as Python, MATLAB and/or Power BI.
• Analyze factors affecting PESS utilization, such as vehicle load (GCW), ambient temperature, driving conditions, drive modes and system inhibitions.
• Identify customer applications and operating conditions with high PESS potential but low actual utilization.
• Quantify lost PESS opportunities and their potential impact on fuel savings.
• Identify and evaluate technical concepts that could extend PESS operation.

The work is not limited to these concepts. An important part of the thesis is to use customer data to discover and prioritize additional improvement opportunities.

Who are you?

We are looking for Master's students within Automotive Engineering, Mechanical Engineering, Mechatronics, Control Engineering, Applied Physics, Data Science or a related field.

You should have:

• Strong analytical and problem-solving skills.
• Experience with data analysis using Python, MATLAB or similar tools.
• Interest in vehicle systems, energy efficiency and data-driven engineering.
• Basic knowledge of statistics and data visualization.
• Ability to connect data findings with physical and engineering phenomena.
• Experience with powertrain systems, energy management, control systems, modelling/simulation, thermal management, MATLAB/Simulink or Power BI is considered an advantage.

Most importantly, we are looking for someone who enjoys using data not only to visualize system performance, but to understand why the system behaves as it does, identify improvement opportunities and quantify their potential.

Number of students - 2 

Last Application Date - 22nd Nov 2026

If you have further questions, you are welcome to contact - Qiyu He, Manager Productivity/Drivability via email qiyu.he@volvo.com
 

We value your data privacy and therefore do not accept applications via mail. 

Who we are and what we believe in 
We are committed to shaping the future landscape of efficient, safe, and sustainable transport solutions. Fulfilling our mission creates countless career opportunities for talents across the group’s leading brands and entities.

Applying to this job offers you the opportunity to join Volvo Group. Every day, you will be working with some of the sharpest and most creative brains in our field to be able to leave our society in better shape for the next generation. ​We are passionate about what we do, and we thrive on teamwork. ​We are almost 100,000 people united around the world by a culture of care, inclusiveness, and empowerment. 

Trucks Technology & Industrial Division hire team players who are ready to create real customer impact. Our decentralized teams work close to our customers, with speed and autonomy, to build what they truly need. 
Join us to collaborate on innovative, sustainable technologies that redefine how we design, build, and deliver value. Bring your curiosity, your expertise, and your collaborative energy, and together, we’ll turn bold ideas into tangible solutions for our customers and contribute to a more sustainable tomorrow.