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조철민(Chulmin Cho),윤한솔(Hansol Yoon),윤헌준(Heonjun Yoon),김홍진(Hongjin Kim),이소원(Sowon Lee),윤병동(Byeng Dong Youn),김재은(Jae Eun Kim),김윤영(Yoon Young Kim) 대한기계학회 2012 대한기계학회 춘추학술대회 Vol.2012 No.11
Prior to designing energy harvesters, it is important to understand ambient energy characteristics and preliminary computation of harvestable energy. With special attention to vibrational and thermal ambient energy sources, this study aims at developing a corresponding energy map that can visualize ambient and harvestable energy). The energy map benefits energy harvesting technology in many ways. First, economic feasibility can be studied while selecting best sites for energy harvesting. Second, the map facilitates the conceptual and detailed design of an energy harvester type (e.g., piezoelectric, thermoelectric) and its target application such as wireless sensor network. The three-fold steps are proposed to build the energy map: 1) data acquisition for available energy, 2) harvestable energy analysis with energy conversion models, and 3) visualization of harvestable energy. We obtain site-specific harvestable energy maps and open discussion about the benefits of the proposed idea.
랜덤 진동 환경에서의 압전 에너지 하베스팅에 대한 통계적 해석
윤헌준(Heonjun Yoon),조철민(Chulmin Cho),윤병동(Byeng Dong Youn) 대한기계학회 2012 대한기계학회 춘추학술대회 Vol.2012 No.11
Vibration energy can be converted into electrical energy using a piezoelectric energy harvester. An analytical model is of great importance to understand the first principle of energy conversion under a given vibration condition. Despite significant effort in developing the analytical models, many have been developed under the assumption of deterministic excitation, which results in unreliable prediction of harvestable power. This paper thus proposes a stochastic framework for piezoelectric energy harvesting analysis. The first step is to estimate a time-varying power spectral density (PSD) of an input random excitation. The second is to select a linear electromechanical model for calculating the voltage response. The final step is to estimate a time-varying PSD of the output voltage. The expected electric power can be estimated by obtaining the autocorrelation function from the time-varying PSD of the output voltage.