IoT deployments continue to progress as organizations pursue digital transformation, and as smart living – in all its forms – holds the key to enhancing quality of life and sustainability.
IoT endpoints tend to be sensors or, less frequently, actuators that are connected wirelessly to an aggregating device or internet gateway. They are often deployed in large numbers and, in a scenario such as smart city, smart factory, or smart agriculture, dispersed over a large geographical area. The cost of carrying out field maintenance, such as replacing discharged primary batteries, is usually prohibitive. In addition, the discarded batteries represent an environmental burden that is increasingly unacceptable.
When designing endpoints, engineers can avoid the need for battery replacement by arranging sufficient energy supply to last for the expected lifetime of the device. This could be several years. A coin cell form factor is usually desirable due to size constraints. If the energy stored falls short of the system requirements, fitting a larger cell may be an option.
An alternative is to redesign the circuitry to reduce the overall system energy demand below the available cell storage. Either approach, or a combination of both, may fail to meet the target.
Micro energy harvesting, in the order of microwatts or milliwatts can provide a useful and potentially inexhaustible supply of electrical energy, captured from the ambient environment. This can supplement or replace a primary cell, depending on the application and the ambient energy available. It may be possible for the harvested and converted energy to power the circuitry directly. On the other hand, storing the energy in a buffer until it is needed can be a more suitable approach.
In any case, a suitable source of ambient energy is required, capable of meeting the needs of the application. Among the various subsystems of the IoT endpoint, the radio places the most significant energy demand. It can be instructive to analyze the requirements here, to inform the design and integration of the energy-harvesting system.
Radio subsystem power consumption
Choosing the most suitable wireless technology to provide the required data rate and communication range at the lowest possible power consumption is critical.
If the sensor is to be positioned only a short distance from an aggregator or gateway such as a hub or router connected to the Internet or through a local telecom exchange, a technology such as Bluetooth, Zigbee, or Wi-Fi may be suitable, depending on the required data rate and also on cost constraints. In other cases, such as where endpoints are distributed over a geographically large area, an LPWAN or cellular connection may be needed. Figure 1 compares the power consumption, data rate, typical maximum range, and relative costs of the major technologies used in IoT applications.
The range, data rate, and power consumption can also be expressed numerically to aid direct comparison. As figure 2 shows, a wireless subsystem can consume from as little as 150µW to 400mW.
To understand fully the effects on the system’s overall energy demand, it is also necessary to consider the duty cycle. Applications such as smart utility meters involve sending small packets of data a few times per day or every few days. Others, such as security cameras, may need to send large amounts of data frequently or continuously. Depending on the application, the duty cycle may be reduced by filtering the data locally within the system before transmitting; a camera may be fitted with a movement sensor to start recording only when activity is detected, or embedded image processing may discard uninteresting data. Of course, the energy needed to filter the data must be compared with the energy saved by reducing the duty cycle, to ensure a net benefit.
Ambient energy sources
Having gained an understanding of the energy and power demanded by the wireless subsystem, it is possible to evaluate suitable ambient sources and micro energy harvesting technologies.
The main micro energy-harvesting technologies suited to powering these systems are arrays of solar cells, piezoelectric or electrostatic converters activated by vibrations, and Peltier devices that convert a temperature gradient into an electromotive force (EMF). RF energy sources captured through patch or coil antennas tend to be unsuitable for all but the most frugal IoT applications. Figure 3 compares the typical energy densities associated with these technologies. Using this information, it is possible to select a technology and begin developing a specification by assessing the sizes and performance of available components.
Solar cells with an area of 35-40cm2 can generate about 0.5 Watts, assuming efficiency of about 20%. These are available for less than 1 USD each in volume, while piezoelectric harvesters are typically at least an order of magnitude more expensive and produce less energy. Solar cells are known to be less efficient when used indoors. However, some indoor solar harvesters have been introduced recently that claim to deliver sufficient output for low-power radios.
Bringing it all together
Leveraging advances such as these, micro energy harvesting can be considered as a solution to reduce or eliminate batteries in IoT endpoints. Because the energy sources themselves are often irregular and not necessarily available when the IoT device needs to transmit or receive data, an energy buffer or storage device is usually needed. This can be a rechargeable battery or capacitor (or supercapacitor). An energy harvesting power management IC (EH PMIC) is needed to handle the energy from the harvesting subsystem, manage the charge supplied to the energy buffer, and power the load when needed, as shown in figure 4. The various energy-harvesting technologies have different electrical characteristics. Thermoelectric harvesters produce continuous DC current at a low voltage and so are low impedance. While solar cells also produce a low DC voltage, the current, and hence impedance, varies with the level of light.
Typical EH PMICS in the market today have a fixed architecture and input voltage range designed to operate with a particular type of harvester. This precludes using an alternative harvester to capture additional ambient energy if one source alone cannot satisfy the system requirement. If several energy sources are needed, therefore, a dedicated EH PMIC is needed for each one. This adds to the system cost, size, and power consumption, and can also complicate the design.
Some EH PMICs can be modified using external circuitry to condition the energy harvester’s output. However, to simplify system design, Trameto’s EH PMICs, called OptiJoule, provide inputs that autonomously adapt to various types of connected harvester and maximize the power delivered to the buffer, without requiring external circuitry. Versions are available for single inputs or with up to four inputs. Multi-input versions feature the flexibility to connect similar or different types of harvesters. So, with OptiJoule devices, it is possible to scale the micro energy harvesting capacity, use a single PMIC for multiple applications, and even delay the selection of energy-harvesting technology until later in a product’s development if needed.
Through developments in optimized radio protocols, low-energy microprocessor design, low power sensors, and the increasing efficiency of micro energy harvesting, ambient energy has become a viable source to help reduce or eliminate reliance on batteries and extend the operating lifetime of IoT endpoints in the field. The latest developments in EH PMICs allow extra flexibility to manage size, cost, and complexity when integrating selected micro energy harvesting technologies.
Huw Davies, CEO and co-founder of Trameto, is a technology business leader with general management, founder roles, product marketing, business development and sales. He has worked in both startups and multi-national corporate organizations. His experience spans global business development, operational and financial management, licensing technology transfer, and collaborative research/commercial partnering. Huw’s background is in semiconductors and consumer electronics, and he has extensive experience of working in Silicon Valley. He holds a BSc and PhD from Cardiff University and an executive MBA from the University of Bath.
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