Design Optimization and Comparison of Cylindrical Electromagnetic Vibration Energy Harvesters

Abstract

Investigating the coil–magnet structure plays a significant role in the design process of the electromagnetic energy harvester due to the effect on the harvester’s performance. In this paper, the performance of four different electromagnetic vibration energy harvesters with cylindrical shapes constrained in the same volume were under investigation. The utilized structures are (i) two opposite polarized magnets spaced by a mild steel; (ii) a Halbach array with three magnets and one coil; (iii) a Halbach array with five magnets and one coil; and (iv) a Halbach array with five magnets and three coils. We utilized a completely automatic optimization procedure with the help of an optimization algorithm implemented in Python, supported by simulations in ANSYS Maxwell and MATLAB Simulink to obtain the maximum output power for each configuration. The simulation results show that the Halbach array with three magnets and one coil is the best for configurations with the Halbach array. Additionally, among all configurations, the harvester with two opposing magnets provides the highest output power and volume power density, while the Halbach array with three magnets and one coil provides the highest mass power density. The paper also demonstrates limitations of using the electromagnetic coupling coefficient as a metric for harvester optimization, if the ultimate goal is maximization of output power.

Unified Modeling and Analysis of Vibration Energy Harvesters under Inertial Loads and Prescribed Displacements

“…The above expression for optimal load resistance for an EMEH, under inertial load, can also be found in [6,14], under the assumption of negligible effect from inductance (β ≈ 0). The term θ 2 /C M in the optimal load for an EMEH, is in [14] defined as the electrical analogue of the mechanical damping.…”

“…In [7], Wang et al performs a similar analysis to that conducted by Arroyo et al [8] (although theirs includes the aspect of harvesting efficiency) but assumes an effective coupling coefficient under the critical value, and thus the anti-resonant point is lost in the analysis. Contrary to [8], Wang et al neglects the intrinsic resistance for the PEH/EMEH (i.e., coil and dielectric resistance), which is common practice for PEHs but is not generally applicable for an EMEH and results in incorrect optimal load resistance [6,14].…”

“…Vibrational energy harvesters (VEHs) based on piezoelectric [1][2][3] or inductive [4][5][6] transduction have been frequently modeled in the previous literature, typically as lumped second-order mass-spring-damper systems. Power output at resonance and anti-resonance, power optimal load and efficiency are typically included in these analyses.…”

An efficient hybrid biomechanical energy harvesting system using human motions for low-power applications

“…The human body's energy is available in thermal, chemical, and mechanical energy sources. To harvest power from these human body sources, there are many energy harvesting mechanisms are available, including triboelectric generator (TEG), piezo-electric ISSN: 2088-8694  analysis of the cylindrical EM vibration-based EHS is presented by Pham et al [27]. The work investigates EM background, coil-magnet structure, optimization methods, design parameters, implementation procedures, and performance analysis.…”

Research on the Directional Adaptability of a Self-Adaptive Energy Harvester

“…WSN consists of tens of thousands of sensor nodes, each of which includes a sensing module, an information processing module, a wireless communication module, a power management module, and a power supply module, where the power supply module supplies power to the other modules and plays a very important role in WSNs [3,4]. In order to provide clean and sustainable electrical energy for WSNs, researchers use various electromechanical conversion mechanisms, such as piezoelectric [5][6][7], electromagnetic [8][9][10], electrostatic [11][12][13], thermoelectric [14][15][16], and triboelectric [17][18][19] mechanisms to convert the vibration energy near the working environment of WSNs into electrical energy. Piezoelectric energy harvesting technology uses the direct piezoelectric effect of piezoelectric materials to realize the conversion of mechanical energy to electrical energy and has high electromechanical conversion efficiency, which has been widely researched by scholars [20,21].…”