Finite element-driven strain energy localization optimization of corrugated multilayer PVDF piezoelectric footstep energy harvesting tiles via Adaptive Quasi-Opposition Hippopotamus Algorithm

Piezoelectric energy harvesting has emerged as a viable approach for converting mechanical energy from pedestrian footsteps into electrical power for self-powered smart infrastructure. The purpose of this study is to prepare and optimize a corrugated multilayer polyvinylidene fluoride (PVDF) piezoelectric energy harvesting footstep tile having improved electromechanical performance. The proposed methodology consists of a corrugated multilayer PVDF structure, finite element-based electromechanical modeling, parametric investigation, design optimization using Adaptive Quasi-Opposition Hippopotamus Algorithm (AQOHA), and validation under realistic footstep loading conditions and feasibility assessment for smart flooring applications. The mechanical analysis indicated that the induced stress rose from 0.31 to 1.01 MPa, and the voltage generated rose from 12.6 to 38.9 V when the footstep force increased from 250 to 750 N. The optimized corrugated geometry improved the output voltage from 18.4 to 41.5 V, while the multilayer configuration increased the generated charge from 14.6 to 42.6 nC and harvested energy from 0.42 to 1.46 mJ. AQOHA optimization achieved an output voltage of 45.9 V, power density of 7.6 mW/cm2, and energy conversion efficiency of 24.7%. The validated design exhibited good stability and high potential for smart flooring and self-powered sensing applications.