A vibration energy harvester can harvest vibration energy in the environment and convert it into electrical energy to power the sensors in the Internet of Things.Human walking contains high-quality vibration energy,wh...A vibration energy harvester can harvest vibration energy in the environment and convert it into electrical energy to power the sensors in the Internet of Things.Human walking contains high-quality vibration energy,which serves as the energy source for vibration energy harvesters due to its abundant availability,high energy conversion efficiency,and environmental friendliness.It is difficult to harvest human walking vibration due to its low frequency.Converting the low-frequency vibration of human walking into high-frequency vibration has attracted attention.In previous studies,vibration energy harvesters typically increase frequency by raising excitation frequency or inducing free vibration.When walking frequency changes,the up-frequency method of raising the excitation frequency changes the voltage frequency,resulting in the best load resistance change and reducing the output power.The up-frequency method of inducing free vibration does not increase the external excitation frequency,which has relatively low output power.This paper designs a magnetostrictive vibration energy harvester with a rotating up-frequency structure.It consists of a rotating up-frequency structure,a magnetostrictive structure,coils,and bias magnets.The main body of the rotating up-frequency structure comprises a torsion bar and a flywheel with a dumbbell-shaped hole.The magnetostrictive structure includes four magnetostrictive metal sheets spliced by Galfenol and steel sheets.The torsion bar and flywheel interact to convert low-frequency linear vibration into rotating high-frequency excitation vibration of the flywheel.The flywheel plucks the magnetostrictive metal sheet with a high excitation frequency to generate free vibration.The vibration energy harvester increases the excitation frequency while inducing free vibration,which can effectively improve the output power.To characterize the excitation vibration and free vibration,based on the theory of Euler-Bernoulli beam theory,the vibration equation of the magnetostrictive metal sheet after being excited is given.According to the classical machine-magnetic coupling model and the Jiles-Atherton physical model,the relationship between stress and magnetization strength is derived.Combined with Faraday's law of electromagnetic induction,the distributed dynamic output voltage model is established.This model can predict the output voltage at different excitation frequencies.Based on this model,the mechanical-magnetic structural parameter optimization design is carried out.The parameters of the magnetostrictive metal sheet,the bias magnet,and the rotating up-frequency structure are determined.A comprehensive experimental system is established to test the device.The peak-to-peak voltage and output voltage signal by the proposed model are compared.The average relative deviation of the peak-to-peak voltage and the output voltage signal is 4.9%and 8.2%,respectively.The experimental results show that the output power is proportional to the excitation frequency.The optimum load resistance is always 800Ωas the excitation frequency changes,simplifying the impedance-matching process.The maximum peak-to-peak voltage of the device is 58.60 V,the maximum root mean square(RMS)voltage is 9.53 V,and the maximum RMS power is 56.20 mW.The magnetostrictive vibration energy harvester with a rotating up-frequency structure solves the problem of impedance matching,which improves the output power.The proposed distributed dynamic output voltage model can effectively predict the output characteristics.This study can provide structural and theoretical guidance for up-frequency structure vibration energy harvesters for human walking vibration.展开更多
Ride and handling are two paramount factors in design and development of vehicle suspension systems. Conflicting trends in ride and handling characteristics propel engineers toward employing multi-objective optimizati...Ride and handling are two paramount factors in design and development of vehicle suspension systems. Conflicting trends in ride and handling characteristics propel engineers toward employing multi-objective optimization methods capable of providing the best trade-off designs compromising both criteria simultaneously. Although many studies have been performed on multi-objective optimization of vehicle suspension system, only a few of them have used probabilistic approaches considering effects of uncertainties in the design. However, it has been proved that optimum point obtained from deterministic optimization without taking into account the effects of uncertainties may lead to high-risk points instead of optimum ones. In this work, reliability-based robust multi-objective optimization of a 5 degree of freedom （5-DOF） vehicle suspension system is performed using method of non-dominated sorting genetic algorithm-II （NSGA-II） in conjunction with Monte Carlo simulation （MCS） to obtain best designs considering both comfort and handling. Road profile is modeled as a random function using power spectral density （PSD） which is in better accordance with reality. To accommodate the robust approach, the variance of all objective functions is also considered to be minimized. Also, to take into account the reliability criterion, a reliability-based constraint is considered in the optimization. A deterministic optimization has also been performed to compare the results with probabilistic study and some other deterministic studies in the literature. In addition, sensitivity analysis has been performed to reveal the effects of different design variables on objective functions. To introduce the best trade-off points from the obtained Pareto fronts, TOPSIS method has been employed. Results show that optimum design point obtained from probabilistic optimization in this work provides better performance while demonstrating very good reliability and robustness. However, other optimum points from deterministic optimizations violate the regarded constraints in the presence of uncertainties.展开更多
基金supported by the National Natural Science Foundation of China(51777053,52077052)。
文摘A vibration energy harvester can harvest vibration energy in the environment and convert it into electrical energy to power the sensors in the Internet of Things.Human walking contains high-quality vibration energy,which serves as the energy source for vibration energy harvesters due to its abundant availability,high energy conversion efficiency,and environmental friendliness.It is difficult to harvest human walking vibration due to its low frequency.Converting the low-frequency vibration of human walking into high-frequency vibration has attracted attention.In previous studies,vibration energy harvesters typically increase frequency by raising excitation frequency or inducing free vibration.When walking frequency changes,the up-frequency method of raising the excitation frequency changes the voltage frequency,resulting in the best load resistance change and reducing the output power.The up-frequency method of inducing free vibration does not increase the external excitation frequency,which has relatively low output power.This paper designs a magnetostrictive vibration energy harvester with a rotating up-frequency structure.It consists of a rotating up-frequency structure,a magnetostrictive structure,coils,and bias magnets.The main body of the rotating up-frequency structure comprises a torsion bar and a flywheel with a dumbbell-shaped hole.The magnetostrictive structure includes four magnetostrictive metal sheets spliced by Galfenol and steel sheets.The torsion bar and flywheel interact to convert low-frequency linear vibration into rotating high-frequency excitation vibration of the flywheel.The flywheel plucks the magnetostrictive metal sheet with a high excitation frequency to generate free vibration.The vibration energy harvester increases the excitation frequency while inducing free vibration,which can effectively improve the output power.To characterize the excitation vibration and free vibration,based on the theory of Euler-Bernoulli beam theory,the vibration equation of the magnetostrictive metal sheet after being excited is given.According to the classical machine-magnetic coupling model and the Jiles-Atherton physical model,the relationship between stress and magnetization strength is derived.Combined with Faraday's law of electromagnetic induction,the distributed dynamic output voltage model is established.This model can predict the output voltage at different excitation frequencies.Based on this model,the mechanical-magnetic structural parameter optimization design is carried out.The parameters of the magnetostrictive metal sheet,the bias magnet,and the rotating up-frequency structure are determined.A comprehensive experimental system is established to test the device.The peak-to-peak voltage and output voltage signal by the proposed model are compared.The average relative deviation of the peak-to-peak voltage and the output voltage signal is 4.9%and 8.2%,respectively.The experimental results show that the output power is proportional to the excitation frequency.The optimum load resistance is always 800Ωas the excitation frequency changes,simplifying the impedance-matching process.The maximum peak-to-peak voltage of the device is 58.60 V,the maximum root mean square(RMS)voltage is 9.53 V,and the maximum RMS power is 56.20 mW.The magnetostrictive vibration energy harvester with a rotating up-frequency structure solves the problem of impedance matching,which improves the output power.The proposed distributed dynamic output voltage model can effectively predict the output characteristics.This study can provide structural and theoretical guidance for up-frequency structure vibration energy harvesters for human walking vibration.
文摘Ride and handling are two paramount factors in design and development of vehicle suspension systems. Conflicting trends in ride and handling characteristics propel engineers toward employing multi-objective optimization methods capable of providing the best trade-off designs compromising both criteria simultaneously. Although many studies have been performed on multi-objective optimization of vehicle suspension system, only a few of them have used probabilistic approaches considering effects of uncertainties in the design. However, it has been proved that optimum point obtained from deterministic optimization without taking into account the effects of uncertainties may lead to high-risk points instead of optimum ones. In this work, reliability-based robust multi-objective optimization of a 5 degree of freedom （5-DOF） vehicle suspension system is performed using method of non-dominated sorting genetic algorithm-II （NSGA-II） in conjunction with Monte Carlo simulation （MCS） to obtain best designs considering both comfort and handling. Road profile is modeled as a random function using power spectral density （PSD） which is in better accordance with reality. To accommodate the robust approach, the variance of all objective functions is also considered to be minimized. Also, to take into account the reliability criterion, a reliability-based constraint is considered in the optimization. A deterministic optimization has also been performed to compare the results with probabilistic study and some other deterministic studies in the literature. In addition, sensitivity analysis has been performed to reveal the effects of different design variables on objective functions. To introduce the best trade-off points from the obtained Pareto fronts, TOPSIS method has been employed. Results show that optimum design point obtained from probabilistic optimization in this work provides better performance while demonstrating very good reliability and robustness. However, other optimum points from deterministic optimizations violate the regarded constraints in the presence of uncertainties.
