A low-frequency resonant electromagnetic vibration energy harvester employing the Halbach arrays for intelligent wireless sensor networks

Wireless Sensors Networks (WSNs) is the critical part of the Internet of Things (IOTs). However, most of the wireless sensors in WSNs also use batteries as their power supply. The finite battery life has limited the development and application of WSNs. The self-powering device could be a good solution, which performs both an energy harvester and wireless sense function. Vibrations with frequencies within 1-50 Hz range are widely available in environment, which makes low-frequency Vibration Energy Harvester (VEH) more useful in WSNs [1, 2]. VEH is typically converted into electrical energy employing electrostatic, piezoelectric and electromagnetic transduction mechanisms [3]. Owing to the advantages of large current and high output power, the electromagnetic VEHs have been a hot research topic at present [4]. In this paper, an electromagnetic VEH employing the Halbach arrays magnetic circuits to convert low-frequency vibration energy into electrical energy is presented. The VEH is made up of the Halbach arrays magnetic circuits, a coil and a cantilever beam. The Halbach arrays magnetic circuits can concentrate the magnetic field on one side while cancelling out the magnetic field on the other side (Fig. 1(a)). An analytical model is developed to analyze the distribution of magnetic field of the Halbach arrays magnetic circuits (Fig. 1(b)). The electric output performances of the proposed VEH have been investigated. Compared to traditional electromagnetic VEH, the proposed VEH can significantly increase output power and energy harvesting efficiency per unit volume. With the enhancement of coil diameter, the peak power of VEH increases sharply first and then decreases gradually. When the diameter of coil is 8 mm, we obtain the optimum output power of 39.8 mW at frequency of 19.5 Hz under 0.5 g acceleration, respectively (Fig. 2). Remarkably, the proposed electromagnetic VEH has great potential for applying in intelligent WSNs, owing to the advantages of improving output power per unit volume in low-frequency vibration.