To wrap things up, we’ll look at how energy harvesting enhances IoT solutions in an industrial setting. We will broadly define industrial applications to be anything related to manufacturing facilities, agriculture, energy infrastructure, and transportation infrastructure.
Like commercial businesses, companies in the industrial space are also driven by cost saving. Although they can benefit from building automation and asset management systems just like commercial businesses, the biggest cost savings for industrial companies come through preventative maintenance and monitoring.
Fixing equipment before a breakdown is much cheaper than after. Breakdowns can also halt production lines, leading to further financial losses. Knowing when equipment is about to breakdown is a vital piece of information.
Before modern electronics, equipment was monitored by visual inspection which was costly, inaccurate, and subject to human error. Today, industrial equipment can be monitored in real-time using sensors. Analytics can be applied to the data produced to predict when a breakdown will occur.
In one case study, a large industrial manufacturer reduced equipment maintenance costs by 66% through predictive vibration analysis.
In many cases, machinery show signs of wear before they completely break down. For example, vibration sensors can detect shifts in resonant frequency, thermal imaging and thermocouples can show changes in temperature, along with many other sensors which can monitor almost every aspect of industrial equipment.
The data produced by these sensors is collected and can be sent to the cloud to be analyzed. Advances in data analytics and machine learning algorithms have made these preventative maintenance systems highly accurate. They can see trends and make conclusions far beyond the ability of a single person.
The Internet of Things enables businesses to make data-driven proactive decisions rather than unforeseen reactive decisions. Manufactures know when their equipment is about to breakdown. Farmers know when their soil needs fertilized or watered before crops die. Oil and gas companies can react faster to leaks. The DOT can know the real-time condition of roads and bridges.
The largest barrier to widespread implementation of these systems is the large initial investment. Wireless sensor networks have removed the need for running wires, greatly reducing installation costs but at the same time introducing battery related on-going maintenance.
Replacing dead batteries in these large wireless sensor networks can represent a significant cost to industrial businesses which lowers long term returns.
Many product developers attempt to fix this problem by extending battery life. This just kicks the bucket down the road. Instead, we need to look at the problem from a different angle. How can we utilize the energy already present in the environment to power these sensing devices?
Energy harvesting techniques can extract power from excess heat or vibrations generated from running equipment, or collect energy from indoor lights or the sun outside. More times than not, these ambient sources can provide more than enough power to run industrial monitoring sensors.
To illustrate how energy harvesting can be implemented in an industrial application, a solar solution for the Sensoterra Moisture Probe will be characterized. This probe measures the moisture level of soil and transmits the data to a gateway which can send it on to the cloud.
It utilizes the LoRa protocol, which is an efficient Low Power Wide Area Network (LPWAN) wireless protocol. LoRa uses an unlicensed band, which means no data subscriptions, and has a range over 10-kilometer line of sight. LPWAN protocols work well for industrial monitoring applications where a single gateway can cover an entire facility, field, or campus and high throughput of data isn’t needed.
The first step in characterizing a solar solution is to determine the power consumption of your device. Previously we used battery lifetime to estimate power consumption, which is quick and easy. Sometimes battery lifetime information isn’t readily available so another way to determine power consumption is based on which wireless protocol you use, how often data is transmitted and how much power the device uses while sleeping or is inactive.
LoRa is designed to be low power. When it's time to transmit, the device will wake up, take a measurement, send the data, and then return to sleep. This whole process only takes 5-10ms. While the device is on, it requires about 10mA of current to operate. While the device is off, the device can require less than 1uA.
To get daily power consumption, we can calculate the energy used per transmission multiplied by the number of transmissions required per day and then add sleep consumption. Assuming we are running a 3V system:
.010A x 3V x .010s / (3600 seconds per hour) = 83nWh per transmission
1uA x 3V x 24h = 72uWh per day
As long as the data transmit period is longer than every couple of minutes, power consumption will be dominated by sleep current.
At a once per hour rate 75uWh per day is a safe estimate.
Next, we can size a custom PowerFilm Electronic Component Panel by considering light conditions and our system voltage. We will use a 3 cell tandem junction module which has an operating voltage of 3.6V. On cloudy days or in shaded areas PowerFilm solar material generates about 1mW/cm^2.
In these conditions, 1cm^2 of solar material would meet this requirement in less than 1 hour per day. This is because the amount of solar power available outdoors is very large compared to state-of-the-art low power electronics.
Next, we need to determine the best charge control circuitry and select a storage element.
For this outdoor application, a supercapacitor will perform well at extreme temperatures and requires less complex charging circuitry. Many wireless ICs are available that accept input voltage from 2-3V, which we can assume for this case. A 3V Low Dropout voltage regulator (LDO) can be used to charge the supercapacitor which can directly power the device.
A 540mF supercapacitor will be able to run the device for about one day without solar.
This is a great example of the potential energy harvesting has in the industrial space. Large networks of low power sensors, which require little to no maintenance, enabling entire industries to operate more efficiently and effectively.
Big data of the future will come from small self-powered devices.
If you want to get ahead of the curve, PowerFilm can work with you to find the best solar harvesting solution for your application.
Contact us and let's get started on a solution today.