کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5477055 | 1521433 | 2017 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Optimum resistance analysis and experimental verification of nonlinear piezoelectric energy harvesting from human motions
ترجمه فارسی عنوان
تحلیل مقاومت بهینه و آزمایش تجربی برداشت انرژی پیزوالکتریک غیرخطی از حرکت انسان
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کلمات کلیدی
برداشت انرژی، پیزوالکتریک، غیر خطی، حرکت انسانی، بهینه مقاومت بار
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی (عمومی)
چکیده انگلیسی
The complex dynamic behavior of nonlinear harvesters make it difficult to identify the optimum mechanical and electrical parameters for maximum output power, when compared to linear energy harvesting devices. In addition, the chaotic and multi-frequencies characteristics of responses under realistic human motion excitations provide additional challenges for enhancing the energy harvesting performance, such as the traditional frequency domain method being inappropriate for optimum resistance selection. This paper provides detailed numerical and experimental investigations into the influence of resistance on the efficiency of nonlinear energy harvesting from human motions. Numerical simulations under human motions indicate that optimum resistance of a nonlinear harvester can be attained to maximize the power output. Moreover, simulations of linear and nonlinear harvesters under harmonic excitations verify the effectiveness of frequency dominant method to obtain optimum resistance in the absence of a change in the dynamic behavior of the harvester. However, numerical simulations and experiments are the effective methods when the harvester shows complex dynamic characteristics. Experimental measurements of harvested power under different motion speeds and resistances are in agreement to the numerical analysis for the nonlinear harvester. The results demonstrate the effectiveness of the proposed resistance optimization method for nonlinear energy harvesting from human motions.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy - Volume 118, 1 January 2017, Pages 221-230
Journal: Energy - Volume 118, 1 January 2017, Pages 221-230
نویسندگان
Wei Wang, Junyi Cao, Chris R. Bowen, Shengxi Zhou, Jing Lin,