FLEET OPTIMIZATION VIA OFF-BOARD MACHINE LEARNING

Background of thesis project


Volvo Construction Equipment, a division of Volvo Group, is one of the world's largest manufacturers of construction equipment such as wheel loaders, dumpers, excavators, road machinery, and compact machines. The production is distributed in Europe, Asia, North America and South America and Volvo CE employs approximately 15000 peoples around the globe. To maintain a leading position, it is important to develop innovative products with high quality and, at the same time, high energy-efficient powertrains.


Suitable background


This MSc thesis is suitable for one or two students that are completing their studies in mechatronics, software or control engineering.
Experience and interest in automotive applications and machine learning is valuable. Own drive, curiosity, ability to analyze and conclude and document is important skills.
The focus of the thesis will be on investigation through data analysis and simulation, implementation, and test on testbench or machine and documentation of algorithms.
The thesis is preferably performed by two master students.

Description of thesis work


Majority of the construction equipment’s operating cycle is repetitive, and a fleet of machines are used to perform the operation. They will be driven along the same path doing the same operation over and over again. Since the operators involved will not be changed often, the way the machine is used will be very similar. In the case of autonomous machines, the machines are driven the same way in the same path. The energy usage, efficiency and usage (including breaks) of the machine will be quite similar among such repetitive cycles. The thesis aims to investigate and propose a method to continuously optimize and improve the operation of a fleet of machines in such repetitive environment.


Thesis Level: Master and/or Bachelor

Language: English


Starting date:
Desired start date is January/February 2023


Number of students:
1-2


Tutor
George Jithin Babu, Electromobility SW architect, +46 16 5414780
https://youtu.be/aUNiVxmiJDE