Control of Hydraulic Hybrid Wheel Loader
Volvo CE, as part of the Volvo Group, has started to investigate further more the hybrid technology as possible solution to reach a high level of efficiency and quality on its off-road vehicles.
This master thesis is suitable for one or two students that are completing their studies in mechatronic systems, vehicular systems or control engineering. The students are preferably skilled in dynamic simulation and optimal control theory. Knowledge in neural networks and machine learning are meriting.
Description of thesis work
The aim of this project is to develop control algorithms for a hydraulic hybrid wheel loader. The students will design and implement efficient control system focusing on the high level energy management strategy taking into account different drive cycles and operating scenarios. One target is to apply online machine learning techniques to control the charging and discharging of the energy storage. Different strategies can be tested and compared and evaluated based on their performance, complexity and computational effort.
The main activities are:
a) Implement a suitable simulation model
b) Define suitable drive cycles representative to the considered wheel loader
b) Design and implement control strategies in Matlab Simulink
d) Evaluate the strategies and give recommendations on online implementation
A full report of the work carried out will be prepared and presented to staff at Volvo CE. It will be required for the students to perform the thesis at Volvo CE facilities in Eskilstuna.
Thesis Level: Master
Starting date: Jan-Feb 2020
Number of students: 2
Tutor: Karl Uebel, +46 16 5418854
Volvo Construction Equipment, Driveline Systems CE42210, TCC11, Eskilstuna
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