Master Thesis - Finding representative road for Full Electric Vehicle operation

Job description

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

 

Many countries and regions have taken on the climate challenge by setting goals to reduce carbon dioxide from transport. Quantifying and reducing carbon dioxide emissions is not only a requirement from legislation but also from customers. CO2 declaration and energy classification systems are continuously developed. However, the actual energy consumption of vehicles depends on the use of the vehicle and thus does not always follow the declared values. The automotive industry has therefore for a long time searched for suitable methods and suitable mathematics to describe transport assignments and actual vehicle use. With the help of such methods and tools, you can ensure that you develop and sell Full Electric Vehicles that match the customer's actual use. The customer receives a vehicle that is not oversized and contains functionality that suits road conditions, transport assignments, traffic, etc. This is considered to lead to energy efficiency both in production and in operation.  Three public founded FFI projects (OCEAN, COVER and U-FEEL), have started this journey by building a strong foundation on which this thesis now will continue.

What you will do

 

Physical tests on road together with simulations are performed to address the right electric powertrain (number of batteries, fuel cell size, motor power, brake power, cooling system size etc) for a customer segment. To keep the development cost down, the number of miles covered by physical tests and simulations should be minimized. The overall objective in this thesis will be to find the shortest road which still represents the full transport missions of a Full Electric Vehicle. The basis of this study is stochastic models and tools developed in the FFI projects mentioned above.

 

The work will include:

 

·  How to describe vehicle actual operation cycles on a high level
·  Identify the GPS coordinates for the operations road network. Split into road segments and filter for unique segments for more efficient data extraction
·  Using GPS coordinates to extract data from road data suppliers (deterministic map data) by reusing/developing already existing tool
·  Identify deterministic data for the stochastic models
·  Build optimization method based on the stochastic models, including weight factor for rating the importance of each segment, for finding a representative road
·  Connect method and tools to a full repeatable process
·  Verification of the result

 

The project will be performed in close collaboration between Volvo Group Trucks Technology (GTT) and Chalmers University.

About you

 

This exciting project is perfect for 1-2 students who are driven, proactive, curious, and persistent. It requires a Master's degree in a relevant engineering field. A keen interest in mathematical modeling, stochastic analysis, and data analytics is essential, along with experience using Matlab and Python. Knowledge of optimization techniques would also be beneficial. Join us in this rewarding opportunity to apply your skills and make a real impact!

Details

 

Project start:  January 2025.  

 

Contact persons:

Rickard Andersson, (Industrial supervisor), Volvo Group Trucks Technology (GTT)
Phone: +46 76 55 33 054

 

Carl Emvin, (Academic supervisor), Chalmers University
Phone: +46 31 772 2313

 

Fredrik Bruzelius, (Examinator & academic supervisor), Chalmers University
Phone: +46 31 772 3628

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

 

Who we are and what we believe in 
Our focus on Inclusion, Diversity, and Equity allows each of us the opportunity to bring our full authentic self to work and thrive by providing a safe and supportive environment, free of harassment and discrimination. We are committed to removing the barriers to entry, which is why we ask that even if you feel you may not meet every qualification on the job description, please apply and let us decide.

 

Applying to this job offers you the opportunity to join Volvo Group . Every day, across the globe, our trucks, buses, engines, construction equipment, financial services, and solutions make modern life possible. We are almost 100,000 people empowered to shape the future landscape of efficient, safe and sustainable transport solutions. Fulfilling our mission creates countless career opportunities for talents with sharp minds and passion across the group’s leading brands and entities. 

 

Group Trucks Technology are seeking talents to help design sustainable transportation solutions for the future. As part of our team, you’ll help us by engineering exciting next-gen technologies and contribute to projects that determine new, sustainable solutions. Bring your love of developing systems, working collaboratively, and your advanced skills to a place where you can make an impact. Join our design shift that leaves society in good shape for the next generation.

Job Category:  Advanced Analytics

Organization:  Group Trucks Technology

Travel Required:  No Travel Required

Requisition ID:  13668