Piezoelectric energy harvesters (PEHs) are widely used to convert energy from a piezoelectric transducer into a stable DC form, which enables low-power IoT devices to have an unlimited operating life without using batteries. Under weak excitation conditions, however, the power-extraction efficiency of conventional PEHs is too low to provide power even to low-power IoT devices that requires low operation voltages less than 2 V. This paper proposes an asymmetric synchronous electric charge extraction (ASECE) scheme that improves the extraction efficiency of PEHs at low output voltages under weak excitation. The proposed ASECE is implemented using 0.18 μm CMOS technology. The figure-ofmerits (FOMs) of the proposed ASECE while operating under 2 V of output voltage are 7.14 and 6.24 at weak and strong excitations, respectively. The maximum FOM for various different excitation levels is observed to be as high as 7.7. The proposed ASECE is superior to prior art with respect to FOM, by at least 1.15×, 1.63×, and 2.21× under 2 V, 1 V, and 0.5 V outputs, respectively, under strong excitation.
As smart grids develop rapidly, low-cost monitoring systems for pole-mounted transformers increase in demand. Even though battery-powered wireless monitoring systems appear to provide optimal solutions, they consume large amounts of energy for continuous sampling and data transmission. Operation and maintenance costs then increase owing to reduced battery lifetime and battery replacement. To overcome this problem, this paper presents an event-driven battery-powered wireless monitoring system that monitors abnormalities of a transformer and transmits data only if an abnormality occurs. When the proposed event controller detects an abnormality, it enables a root mean square (RMS) converter and a peak detector for sampling and transmitting the maximum RMS value of the abnormal signal and then falls into sleep mode until the next event to save energy. Simulation and experimental results show that the proposed system enhances battery lifetime by up to two orders of magnitude compared to a conventional battery-powered wireless monitoring system.
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