Date of Award
Doctor of Philosophy (PhD)
Electrical, Computer & Energy Engineering
Advances in semi-conductor technology have led to the reduction in size and power consumption of microelectronic circuits. With the miniaturization and increased efficiency of these circuits there are more potential applications for wireless sensor networks and portable electronic equipment. These applications include structural integrity and environment monitoring such as aircraft wing health monitoring and forest fire and natural disaster detection. Biomedical devices have also benefited from the improved size and performance of microelectronics. This thesis studies power management techniques to enable efficient energy scavenging at micropower input power levels from a number of power sources. These sources range from temperature gradients, radio frequency (RF) radiation, solar power, and mechanical vibrations. The scavenged energy is used to improve the performance and distribution of wireless sensors and devices by supplementing or potentially replacing the local power supply of the sensor or device. The major focus of this thesis is to combine source characterization, power management theory, detailed power loss analysis, and ultra-low power circuit design to maximize the extraction of energy from source and deliver it to the wireless sensor or device. The resistor emulation techniques from power factor correction (PFC) are leveraged to load an RF rectifying antenna (rectenna) such that maximum power point tracking (MPPT) of the rectenna is achieved naturally. An application specific integrated circuit (ASIC) is developed to implement this technique after experimental verification with commercially available discrete circuitry. Experimental results show efficient energy scavenging at power levels below 2 microwatts. In addition to resistor emulation, synchronous electric charge extraction (SECE) for energy scavenging from piezoelectric generators is also investigated. The presented techniques allow for the scavenging of usable power for sensors at power levels significantly lower than previous research.
Paing, Thurein Soe, "Power Management Techniques for Micropower Energy Scavenging" (2012). Electrical, Computer & Energy Engineering Graduate Theses & Dissertations. 34.