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Self-sensing state estimation of switch-controlled energy harvesters

Yushin Hara, Yuta Yamamoto, Kanjuro Makihara

2020Journal of Intelligent Material Systems and Structures22 citationsDOI

Abstract

Vibration energy harvesters are expected to become a new source of electrical power. Piezoelectric vibration energy harvesters that employ a piezoelectric transducer, a rectifier, and a storage capacitor are being used widely as electro-mechanical harvesters. Synchronized switch harvesting on inductor enhances harvesting performance due to employing a simple additional circuit and incorporating suitable switch control functionality. Switching is usually based on the displacement of a vibrating structure; hence, sensing the vibrational states is of critical importance. Conventionally, the structural displacement is measured by displacement sensors or accelerometers attached to the target vibrating structure. Although enhancement of performance through synchronized switch harvesting on inductor equipped with sensors is important, the arrangement requirements of sensors have adverse effects on the compactness and usability of the harvesters. This study aimed to eliminate the use of sensors from switch-controlled harvesters. We developed a new state estimation method that uses the piezoelectric transducer’s voltage as an observation value. Using the proposed state estimation method, the modal state values of the vibrating structure can be determined by simply measuring the voltage of the transducer. With the switch device being controlled by the estimated modal state values, no sensors are required for ensuring effective harvesting. A comparison of the harvesting performances by the proposed self-sensing state estimation method and the conventional sensor-equipped state estimation method showed that there is little difference in harvested power between the two methods over a wide range of load resistances. The proposed method is superior to the sensor-equipped method in terms of compactness and usability as it does not require any external sensors.

Topics & Concepts

Energy harvestingVibrationVoltageTransducerRectifier (neural networks)CapacitorInductorPiezoelectricityEngineeringPower (physics)Electronic engineeringEnergy (signal processing)AcousticsElectrical engineeringComputer scienceMathematicsMachine learningRecurrent neural networkStatisticsArtificial neural networkQuantum mechanicsStochastic neural networkPhysicsInnovative Energy Harvesting TechnologiesStructural Health Monitoring TechniquesSmart Materials for Construction
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