Energy harvesting is becoming increasingly important in low-power applications where energy from the environment is used to power the system alone, or to supplement a battery. For example, pulse oximeter sensors inside helmets of road racing cyclists are powered by the sun. These sensors have become smaller and more practical without the limitation of a finite energy supply. Harvested energy from an energy transducer (solar, piezoelectric, etc.) must be maximized to ensure these devices can survive periods where environmental energy is scarce. The conversion process from the transducer to usable power for the device is not perfectly efficient. Specifically, the output voltage of a solar cell is a function of the light intensity, and by extension the load it powers. A small perturbation of the light source quickly diminishes the available power. The wasted power reduces the energy available for the application, and can be improved using an approach called maximum power point tracking (MPPT). This technique maximizes harvesting efficiency by dynamically impedance matching the transducer to its load. This report introduces the Maximum Efficient Solar Harvester (MESH), an MPPT algorithm tuned for a specific Wireless Sensor Network (WSN) application. MESH specifically controls the operation of the DC-DC converter in a solar power management unit (PMU). The control is done by monitoring the available light and feeding that information to choose the optimal operating point DC-DC converter. This operating point has a direct dependency on the overall efficiency of the system. For MESH to be practical, the cost and power overhead of adding this functionality must be assessed. Empirical results indicate that MESH improves the maximum efficiency of the popular Texas Instruments (TI) RF2500-SEH WSN platform by an average of 20%, which far exceeds the power overhead it incurs. The cost is also found to be minimal, as WSN platforms already include a large portion of the hardware required to implement MESH. The report was done in collaboration with Stephen Kobdish. It covers the software implementation and MESH architecture definition; Kobdish's companion report focuses on hardware components and the bench automation environment. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/26625 |
| Date | 16 October 2014 |
| Creators | Rais, Shahil Bin |
| Source Sets | University of Texas |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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