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dc.creatorPertin, Osor
dc.creatorGuha, Koushik
dc.creatorJakšić, Olga
dc.date.accessioned2021-10-13T06:21:15Z
dc.date.available2021-10-13T06:21:15Z
dc.date.issued2021
dc.identifier.issn2079-3197
dc.identifier.urihttps://cer.ihtm.bg.ac.rs/handle/123456789/4784
dc.description.abstractThis paper presents a study on the design and multiobjective optimization of a bimorph-segmented linearly tapered piezoelectric harvester for low-frequency and multimode vibration energy harvesting. The procedure starts with a significant number of FEM simulations of the structure with different geometric dimensions—length, width, and tapering ratio. The datasets train the artificial neural network (ANN) that provides the fitting function to be modified and used in algorithms for optimization, aiming to achieve minimal resonant frequency and maximal generated power. Levenberg–Marquardt (LM) and scaled conjugate gradient (SCG) methods were used to train the ANN, then the goal attainment method (GAM) and genetic algorithm (GA) were used for optimi-zation. The dominant solution resulted from optimization by the genetic algorithm integrated with the ANN fitting function obtained by the SCG training method. The optimal piezoelectric harvester is 121.3 mm long and 71.56 mm wide and has a taper ratio of 0.7682. It ensures over five times greater output power at frequencies below 200 Hz, which benefits the low frequency of the vibration spectrum. The optimized design can harness the power of higher-resonance modes for multimode applications.sr
dc.language.isoensr
dc.publisherMDPIsr
dc.relationinfo:eu-repo/grantAgreement/MESTD/inst-2020/200026/RS//sr
dc.rightsopenAccesssr
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceComputationsr
dc.subjectArtificial intelligencesr
dc.subjectMEMSsr
dc.subjectVibration energy harvestersr
dc.titleArtificial intelligence-based optimization of a bimorph-segmented tapered piezoelectric mems energy harvester for multimode operationsr
dc.typearticlesr
dc.rights.licenseBYsr
dcterms.abstractПертин, Осор; Гуха, Коусхик; Јакшић, Олга;
dc.citation.volume9
dc.citation.issue8
dc.citation.spage84
dc.identifier.doi10.3390/computation9080084
dc.identifier.fulltexthttps://cer.ihtm.bg.ac.rs/bitstream/id/20887/computation-09-00084-v3.pdf
dc.identifier.scopus2-s2.0-85112600772
dc.identifier.wos000688890900001
dc.type.versionpublishedVersionsr


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