Cantilevered Piezoelectric Micro Generator Design Issues and Application to the Mining Locomotive

Abstract

This paper will present a complete discussion in recent design strategies for harvesting vibration energy using piezoelectric cantilever transducers. The interest in this primary energy source is due to its presence in non-negligible quantities in most of the engines used in the industrial process. Previous work has shown that it is possible to harvest significant amounts of energy capable of supplying a wireless sensor (WS) node. However, in most research, only one step of the energy conversion and utilization chain is studied. Starting from the definition of the different design issues for a piezoelectric micro generator (PMG), the leading optimization solutions will be reviewed in this paper. Based on the findings, the quantification of the data transmission range of wireless sensor nodes powered by a PMG is proposed to support the objectives envisioned by Industry 4.0. The vibration characteristics taken from mining locomotives that have not yet been treated previously are used to illustrate the improvement of the various optimization solutions. Through our objectives, this work offers a comprehensive discussion on the use of vibrational energy by wireless sensors, bringing together the fields of mechanics, electrical, electronics, and wireless communications. The theoretical basis for each design stage is provided through the design equations. Based on actual measurements of ambient vibration, it is demonstrated, considering an optimal design of the PMG, that a WS could transmit data beyond 1 km for physical phenomena to be controlled every 7 min.Energies 2020, 13, 63 2 of 28The data collected by WS are transmitted wirelessly to BS. Given the advantages offered by the WS, namely flexibility, ease of deployment, low cost, they are now playing a vital role in the industry 4.0 [8]. More specifically, in the industrial environment, WSs are used in the automation system [9], operations control, system monitoring (humidity, temperature, fire alarm, dust index, toxic gas, and pollution) [9,10], and motion control [11]. In most of these industrial applications, WSs are placed in difficult-to-access locations (mining crushers for example) and maintenance operations for the replacement of batteries can be costly.This issue of energy autonomy of WSs has given rise in recent years to a new field of research known as energy harvesting (EH) [12]. Energy harvesting is the process of converting ambient energy into electrical energy; the most targeted application is the power supply of the WSs.EH technologies differ from one another depending on the nature of the used primary energy source. The main considered sources are the internal light, electromagnetic energy, vibration, and heat [13]. Among these primary sources, vibration abounds in the industrial applications due to the many engines used in most processes [14]. Concerning the specific case of the mining industry, crushers that operate 24 h a day, mining locomotives for the transport of personnel and minerals, trucks, are examples of sources of vibration.A lot of rese...

Piezoelectric Energy Harvesting Prediction and Efficient Management for Industrial Wireless Sensor

“…The same observation can be made for the study in [38]. In [19] by considering most PT optimization solutions (in particular the SSHI technique), it is obtained that the vibrations took at a given moment in a mining locomotive make it possible to transmit data every 7 min at only 958 m, unlike every 1 min to 3 km as is the case in our study.…”

“…For example, in [38], it took 12 h of charging on a 0.33 pF capacitor before the sensor was able to transmit data. In [19], only 512 bits was transmissible every 7 min at less than one kilometer. This poor QoS is because most of the consumption models considered for stand-alone IWSs are based on short-range communication modules like the CC2520 from Texas Instruments.…”

“…Very often, the method allows the node to operate perpetually, but this is to the detriment of the Quality of Service (QoS) since it is difficult to predict the frequency of data transmission and the amount of data that the IWS can transmit at a given time. For example, in [19], the vibration data from a mining locomotive are used to design a piezoelectric micro-generator, which incorporates most of the optimizations proposed in the literature, in particular, the non-linear SSHI technique. The designed circuit allowed an IWS to transmit data with 512 bits at less than a kilometer every 7 min.…”

Recent Advancements in IoT Implementation for Environmental, Safety, and Production Monitoring in Underground Mines

“…So far, piezoelectric energy harvesting has demonstrated the ability to generate sufficient energy to power a wireless sensor node. Mouapi et al [126] designed a cantilevered piezoelectric energy harvester to scavenge the vibration of an operating mining locomotive. The recorded vibration data indicated that the test locomotive produced random vibrations with a dominant acceleration of 0.72 g at a frequency of 21.88 Hz.…”