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The intrinsic characteristic of piezoelectric actuators (PEA), known as hysteresis, has been demonstrated to diminish the capability and stability of the system significantly. This paper proposes a modified-generalized Prandtl-Ishlinskii (MGPI) model to describe the rate-dependent hysteresis in piezoelectric actuators. The developed model incorpo-rates a voltage change rate function to replace the first part of the generalized Prandtl-Ishlinskii (GPI) model. Additionally, the model integrates the cubic polynomial into the envelope function, along with the dynamic thresholds and weights. When describing the hysteresis of the piezoelectric actuator (PEA), the model parameters are identified using the Improved Grey Wolf Optimizer (IGWO) algorithm. To prevent the algorithm from getting trapped in local optima, the cubic chaotic mapping is utilized for population initialization, as well as a nonlinear convergence factor, and the Levy flight strategy factor is introduced to update the Wolf pack's position. The rate-dependent hysteresis behavior of a PEA under excitation in the 1~200 Hz frequency range was experimentally meas-ured. The measured data were used to demonstrate the validity of the proposed MGPI model. The relative root-mean-square error and the relative maximum error of the MGPI model are 1.41% and 6.00%, respectively, which are lower than those of the GPI model, which are 3.15% and 10.58%. Under the composite frequency driving, the outputs of the GPI model and MGPI model were compared with the measured data of the PEA, the results suggest that the MGPI model and the IGWO algorithm can more accurately describe the rate-dependent hysteresis of the piezoelectric actuators.
The intrinsic characteristic of piezoelectric actuators (PEA), known as hysteresis, has been demonstrated to diminish the capability and stability of the system significantly. This paper proposes a modified-generalized Prandtl-Ishlinskii (MGPI) model to describe the rate-dependent hysteresis in piezoelectric actuators. The developed model incorpo-rates a voltage change rate function to replace the first part of the generalized Prandtl-Ishlinskii (GPI) model. Additionally, the model integrates the cubic polynomial into the envelope function, along with the dynamic thresholds and weights. When describing the hysteresis of the piezoelectric actuator (PEA), the model parameters are identified using the Improved Grey Wolf Optimizer (IGWO) algorithm. To prevent the algorithm from getting trapped in local optima, the cubic chaotic mapping is utilized for population initialization, as well as a nonlinear convergence factor, and the Levy flight strategy factor is introduced to update the Wolf pack's position. The rate-dependent hysteresis behavior of a PEA under excitation in the 1~200 Hz frequency range was experimentally meas-ured. The measured data were used to demonstrate the validity of the proposed MGPI model. The relative root-mean-square error and the relative maximum error of the MGPI model are 1.41% and 6.00%, respectively, which are lower than those of the GPI model, which are 3.15% and 10.58%. Under the composite frequency driving, the outputs of the GPI model and MGPI model were compared with the measured data of the PEA, the results suggest that the MGPI model and the IGWO algorithm can more accurately describe the rate-dependent hysteresis of the piezoelectric actuators.
The reduction in the supply of fossil fuel available, combined with global warming’s effects on the atmosphere, has led to the discovery of employing sustainable energy for everyday activities. Road energy harvesting is one example of sustainable energy that can be used, as the majority of people spend a substantial amount of their daily activities commuting from one location to another, and numerous types of transportation generate heat that can be converted into energy. This alternative energy source can be implemented on the road, considering that roads are critical infrastructure that has a significant effect on a country’s economy. Furthermore, road infrastructure has been contributing towards the affordability of urbanization and migration, whether locally or internationally. Currently, researchers are working towards integrating road energy harvesting around the world by incorporating various types of materials and technology connected via a sensing system. Many materials have been attempted, including ceramics, polymers, lead-free, nanomaterials, single crystals, and composites. Other possible sources to generate energy from roadways, such as solar power, thermal energy, and kinetic energy, have been investigated as well. However, many studies available only focused on the disclosure of novel materials or the review of technologies produced for road energy harvesting. There have been limited studies that focused on a comprehensive review of various materials and technologies and their implications for the performance of road energy harvesting. Hence, the main objective of this research is to undertake a thorough and in-depth review in order to identify the best materials and technologies for certain types of application in road energy harvesting. The paper discusses energy-harvesting technology, sensing systems, and the potential network based on them. Comprehensive analyses were conducted to evaluate in-depth comparisons between different materials and technologies used for road energy harvesting. The novelty of this study is related to the appropriate efficient, durable, and sustainable materials and technologies for their relevant potential application. The results of this review paper are original since it is the first of its kind, and, to the best knowledge of the authors’ knowledge, a similar study is not available in the open literature.
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