Analysis and modification of a common energy harvesting system using magnetic shape memory alloys

Salarieh, Hassan; Mehrabi, Mohammadmahdi; Hoviattalab, Maryam

doi:10.1177/1045389x20963174

Cited by 3 publications

(3 citation statements)

References 30 publications

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“…where N is the number of turns of the pick-up coil, ∆Φ B is the change in magnetic flux, A is the constant cross-sectional area of the coil, ∆B max is the maximum change in magnetic flux density over the time increment ∆t [30][31][32].…”

Section: Data Availability Statementmentioning

confidence: 99%

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On the power and efficiency of Ni₂MnGa magnetic shape memory alloy power harvesters

D’Silva¹,

Feigenbaum²,

Ciocanel³

2022

Smart Mater. Struct.

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The martensite variant reorientation in Ni2MnGa magnetic shape memory alloys (MSMAs) causes a change in their bulk magnetization, that can be harvested into useful voltage/power by means of a pick-up coil. The coil may be placed directly surrounding an MSMA element or to the side of the MSMA element wrapped around a magnetic core. This paper reports new power harvesting data generated with a bi-axial magnetic field and a surrounding coil and full strain field data for an MSMA subject to load similar to what is seen during power harvesting, then compares the performance of MSMA-based power harvesters with different designs to determine which give the best output. For this comparison, we provide a framework for evaluating the performance of MSMA-based power harvesters reported in the literature. This framework involves normalizing the results to the design characteristics of the respective harvesters, i.e. number of turns of the pickup coil, cross-sectional area of the pickup coil, frequency of excitation, and sample size, to allow for a direct comparison of power harvesters’ output. Results show that power harvesting with the bi-axial field and a surrounding coil does not generate as much power as previously thought. The strain maps reveal the potential for perpendicular twin boundaries that block each other’s motion limiting variant reorientation and correspondingly the harvester’s power output. The paper concludes that the largest change in magnetic flux density, which is the driver for power harvesting, occurs in the side coil setup with an optimized magnetic circuit and it recommends using this configuration for future MSMA-based power harvester designs for maximum power output.

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Section: Data Availability Statementmentioning

confidence: 99%

“…where Z is the impedance of the load [31,35]. Thus, the maximum power density per cycle, P density−max , can be calculated from the peak electrical power and the volume of the MSMA sample as…”

Section: Data Availability Statementmentioning

confidence: 99%

On the power and efficiency of Ni₂MnGa magnetic shape memory alloy power harvesters

D’Silva¹,

Feigenbaum²,

Ciocanel³

2022

Smart Mater. Struct.

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show abstract

“…Sayyaadi [9] constructed an MSMA-based energy harvester, augmenting the maximum voltage acquisition power by 30 % within an improved system under a bias field of 0.55 T, revealing a nonlinear relationship between the acquisition voltage and the strain rate. Hassan Sayyaadi proposed a model for simulating the process of accessing magnetic shape-memory alloys during vibration energy acquisition.…”

Section: Introductionmentioning

confidence: 99%

Designing and modeling of a new MSMA vibration energy transducer

Luping,

Jing,

Yunhong

2024

J. vibroeng.

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The conversion of mechanical vibrational energy into electrical energy to power wireless electronic devices using the smart material magnetic shape memory alloy (MSMA) has garnered substantial attention. This paper presents a vibration energy transducer founded on the inverse effect of MSMA, elucidating the principle of power generation. The variations in martensite and magnetic domain characteristics within MSMA were analyzed, and a constitutive model was established for the MSMA vibration energy transducer, integrating the thermodynamic theory of the Gibbs free energy function. Although this model performs well in predicting experimental outcomes, it falls short in capturing all features of the experimental data. To comprehensively encompass these features, the PSO-XGBoost machine learning approach was introduced to train the experimental data by incorporating factors such as stress, magnetic field, and induced voltage. An experimental prototype of the MSMA vibration energy transducer is fabricated, and the predictions of both models are compared with the collected experimental data, validating the accuracy of the model and indicating the enhanced effectiveness of machine learning methods in prediction. This research not only validates the correctness of the models but also emphasizes the potential for more precise predictions using machine learning methods, thereby establishing a robust foundation for the thorough study and broader application of MSMA vibration energy transducers.

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Nonlinear Dynamics of a Magnetic Shape Memory Alloy Oscillator

Souza,

Monteiro,

Savi

2024

Journal of Computational and Nonlinear Dynamics

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Magnetic shape memory alloys (MSMAs) constitute a class of smart materials capable of exhibiting large magnetic field induced strain (MFIS) when subjected to magnetomechanical loadings. Two distinct mechanisms are responsible for the induced strain: martensitic variant reorientation and phase transformation. The martensitic reorientation is the most explored mechanism presenting the advantage to potential provide high-frequency actuation since it does not rely on phase transformation cycles. Despite its capabilities and potential dynamical applications, the dynamical behavior of MSMAs is not extensively explored in the literature that is usually focused on quasi-static behavior. Thereby, the objective of this work is to analyze the nonlinear dynamics of MSMAs. In this regard, an MSMA nonlinear oscillator is investigated, exploiting the system response under different bias magnetic field levels and actuation frequencies. A phenomenological model is employed to describe the MSMA magnetomechanical behavior. Numerical simulations are carried out using the operator split technique together with an iterative process and the fourth-order Runge–Kutta method. Results show that the application of a bias magnetic field can reduce the mean displacement of the system, increasing the oscillation amplitude. Furthermore, the period of oscillation can be modified, even achieving complex behaviors, including chaos. The potential use of MSMAs to dynamical systems is explored showing the possibility to provide adaptive behaviors.

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Analysis and modification of a common energy harvesting system using magnetic shape memory alloys

Cited by 3 publications

References 30 publications

On the power and efficiency of Ni₂MnGa magnetic shape memory alloy power harvesters

On the power and efficiency of Ni₂MnGa magnetic shape memory alloy power harvesters

Designing and modeling of a new MSMA vibration energy transducer

Nonlinear Dynamics of a Magnetic Shape Memory Alloy Oscillator

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Analysis and modification of a common energy harvesting system using magnetic shape memory alloys

Cited by 3 publications

References 30 publications

On the power and efficiency of Ni2MnGa magnetic shape memory alloy power harvesters

On the power and efficiency of Ni2MnGa magnetic shape memory alloy power harvesters

Designing and modeling of a new MSMA vibration energy transducer

Nonlinear Dynamics of a Magnetic Shape Memory Alloy Oscillator

Contact Info

Product

Resources

About

On the power and efficiency of Ni₂MnGa magnetic shape memory alloy power harvesters

On the power and efficiency of Ni₂MnGa magnetic shape memory alloy power harvesters