The modern advances in wireless technology and low-power electronics has brought a variety of wireless sensors in market recently; however, the limited lifespan and high replacement cost of batteries make it difficult to fully utilize performance of wireless sensors. Energy harvesting (EH) technology that harvests electrical energy from the ambient vibration energy has been emerged as an ultimate solution to prolong the battery life or eliminate the need of batteries for wireless sensors. Energy harvesting (EH) skin is one of the EH devices that generates electrical energy from the vibrating skin structure with an additional thin piezoelectric layer as one embodiment. As long as the power level of EH skin does not far exceed required one of wireless sensors, the key design consideration must be reliable power generation through the life of wireless sensors regardless of uncertainty and/or variation in material property, boundary condition, excitation etc. This paper presents a framework of statistical model calibration to develop a stochastic computer model for robust and reliable EH skin design. The framework consists of two different hierarchical levels: (1) bottom-level calibration with mechanical response and (2) top-level calibration with electrical response. Cantilever-type energy harvesters are used to demonstrate the statistical calibration framework. The statistical calibration employs uncertainty propagation analysis, optimization and likelihood metric to obtain unknown model variables such as compliance (s 11 ), piezoelectric strain coefficient (d 31 ) and permittivity (ε 33 ). With a computer model after model calibration, the EH skin was designed to generate maximum power and the probability density function (PDF) of predicted power is calculated and verified by experiments. Finally, a prototype of the EH skin was manufactured and demonstrated to operate wireless temperature sensors for structural health monitoring and/or building automation. It is conclude that the EH skin can generates enough power to operate many wireless sensors for building automation, smart plant and/or structural health monitoring. Nomenclatures 11 = compliance d 31 = piezoelectric strain constant ε 33 = permittivity θ = unknown model variable vectors 1 Senior researcher, The 1 st R&D Institute, bcjung79@gmail.com. 2 Master student, School of Mechanical and Aerospace Engineering, odyssey44@naver.com, AIAA student member. 3 Master student, School of Mechanical and Aerospace Engineering, heonjun@snu.ac.kr, AIAA student member. 4

This paper presents an innovative design platform of piezoelectric energy harvester (EH), named segment-type EH, and its application to a wireless sensor. Energy harvesting technology is motivated to minimize battery replacement cost for wireless sensors, which aims at developing self-powered sensors by utilizing ambient energy sources. Vibration energy is one of widely available ambient energy sources which can be converted into electrical energy using a piezoelectric material. The current state-of-the-art in piezoelectric EH technology mainly utilizes a single natural frequency which is less effective when utilizing a random ambient vibration with multimodal frequencies. This research thus proposes the segment-type harvester to generate electric power efficiently which utilizes multiple modes by separating the piezoelectric material. In order to reflect the random nature of ambient vibration energy, a stochastic design optimization is solved to determine the optimal configuration in terms of energy efficiency and durability. A prototype is manufactured and mounted on a heating, ventilation, air conditioning (HVAC) system to operate a temperature wireless sensor. It shows its excellent performance to generate sufficient power for a real time temperature monitoring for building automation.

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