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Scania is a world-leading provider of transport solutions. Together with our partners and customers we are driving the shift towards a sustainable transport system. In 2017, we delivered 82 500 trucks, 8 300 buses as well as 8 500 industrial and marine engines to our customers. Net sales totalled nearly SEK 120 billion, of which about 20 percent were services-related. Founded in 1891, Scania now operates in more than 100 countries and employs some 49 000 people. Research and development are concentrated in Sweden, with branches in Brazil and India. Production takes place in Europe, Latin America and Asia, with regional production centres in Africa, Asia and Eurasia. Scania is part of Traton Group. For more information visit www.scania.com.
Thesis project at Scania is an excellent way of making contacts for your future working life. Many of our current employees started their career with a thesis project.
Background:
Hybrid and electric propulsion vehicles are taking market shares all around the world. To be able to compete Scania is offering hybrid trucks as well as electric busses. It is critical for safety, performance and product cost to be able to accurately monitor the state of high-voltage battery packs. One important characteristic to monitor is remaining capacity (Ah) as it is known to decrease over the life of the battery due to aging mechanism and wear.
The candidate have a background in engineering and have experience with programming languages such as Matlab or Python. The candidate have experience from one or more of the fields: Control theory, Mathematical modeling, Data analytics, Statistics, Battery chemistry, Machine learning, Other.
Target:
The goal is to investigate the properties of capacity estimation using a preferred approach to be discussed later.
Assignment:
The candidate will work in cooperation with Scania engineers, at R&D office in Södertälje. The goal is to investigate the properties of capacity estimation using a preferred approach to be discussed later. The properties to be evaluated are accuracy, robustness and suitability for embedded controller implementation.
Education:
Specify education or specialisation: Master od Sience, electrical engineering
(have experience from one or more of the fields: Control theory, Mathematical modeling, Data analytics, Statistics, Battery chemistry, Machine learning, Other. )
Number of students: 1
Start date: flexible
Estimated time needed: 6 month
Contact persons and supervisors:
Johan Lundström, NEBS, +46 8 553 85 551
Göran Lissel, NEBS, +46 70 0860 984
Your application should contain a covering letter, CV and transcripts.
Selections will be made throughout the application period.
24-03-2024
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