Resumen
Piezoelectric energy harvesting from roadways, which converts ambient vibration energy of roads into electric energy, has a wide range of potential applications in intelligent transportation systems. On-site open-traffic tests revealed that energy harvested by piezoelectric energy harvester (PEH) units embedded in roadways is far less than the value in laboratories, which may be because the parameters of traffic flow load (frequency, distribution, wave shape, etc.) and the road structure are significantly different from the pre-established conditions in laboratories or even on-site tests with only one vehicle passing. To address this issue, an analytical model for piezoelectric energy harvesting from roadways under open-traffic conditions was proposed to examine the mechanical response of the road structure and the electrical performance of the stack PEH units embedded in the road. The influence of all parameters in the energy-harvesting system was then obtained with the scaling law method, revealing that the energy harvested by PEH units is determined by the energy coefficient, the system?s intrinsic parameter, normalized parameters of roadways, and the normalized embedded position of PEH units. It is found that that the energy-harvesting system?s intrinsic parameter should be approximately 0.8 to ensure maximum energy-harvesting efficiency. Meanwhile, the pavement with lower bending stiffness and higher linear density while the foundation with small stiffness and smaller damping coefficient would be more suitable for energy harvesting. Furthermore, the lateral embedded position of PEH units should be carefully chosen, since the units embedded in an optimal position can harvest three times more than that embedded in other positions. The concise criteria presented in this study will be used as a reference not only for material selection, dimension optimization, and embedded positions determination of PEH units but also for choosing of the optimal roadways to achieve maximum piezoelectric energy harvesting efficiency under open-traffic conditions.