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Photovoltaic Energy Management for an autonomous electric vehicle


M. Stettler

Semester/Bachelor Thesis, SS 09

At the Automatic Control Laboratory at the Swiss Federal Institute of Technology (ETH) Zurich, a reduced scale solar vehicle is going to be designed and built in order to test and apply up to date control techniques, which then are intended to be upscaled to real vehicles. The vehicle has to be able to drive autonomously, without any energy provided by external sources. The energy for the motors and the controllers to run is allocated by a photovoltaic (PV) array and stored in batteries and ultracapacitors. In this semester project, the PV panel, the corresponding power converter and its control is designed and implemented. Because the power generation of the PV array depends on external conditions, e.g. solar irradiation and cell temperature, it has to be controlled in order to operate the array at the optimal point, the Maximal Power Point (MPP). Such control techniques are called Maximum Power Point Tracking (MPPT) algorithms. Various MPPT algorithms are reviewed and compared, and one of them is selected for implementation. The implemented control algorithm is a Perturb and Observe algorithm which is able to track the PV panel to operate at its MPP. The implemented algorithm is showing good results, both in steady state and in transient conditions. The algorithm is able to track the constructed PV panel to the MPP, allowing it to deliver a maximal energy output needed for the vehicle’s autonomous motion. In order to improve the panel’s energy production, other reviewed algorithms should be implemented and compared in a next step. After this comparison, the best fitting algorithm should be implemented on the PV panel.


Type of Publication:

(13)Semester/Bachelor Thesis

S. Mariéthoz

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2009:IFA_3397
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