Harvest energy for your IoT platform
January 30, 2018
Kinetic energy in different forms (lateral movement, rotation, or vibration) has long been used to generate electrical energy using electromagnetic or piezoelectric harvesters.
The IoT combines input data, processing resources, and actuators to enable new applications. Delivering relevant input data is therefore a central requirement. For developers, energy harvesting wireless sensors are of special interest as they offer flexible radio communication while eliminating the need for maintenance. Such sensors have seen a dramatic rise in interest, as they’re a reliable, easy to install technology that delivers the essential input data on which the whole IoT model depends.
Creating a sensor node that fulfills the essential data capture, processing, and transmission within the minimal energy that can be harvested from the environment is a challenge. There are three key tasks in energy harvesting wireless sensors: generating (harvesting) the required energy, sensing and processing environmental parameters (e.g. temperature, humidity, position), and wirelessly transmitting the collected information. All three tasks need to be optimized together to provide viable solutions.
Kinetic energy in different forms (lateral movement, rotation, or vibration) has long been used to generate electrical energy using electromagnetic or piezoelectric harvesters. For most applications, the electromagnetic energy harvester is the better choice as it provides a more stable energy output at a longer lifecycle without ageing effects. These harvesters generally work by changing the magnetic flux through a coil, either by moving a magnet relative to the coil or by changing the flux polarity. The latter approach is used in EnOcean’s ECO 200 harvester, which can quickly switch magnetic polarity based on lateral movement of its spring. This type of kinetic energy harvesting is the technology of choice for mechanical switches and similar applications.
Many sensor applications are powered by miniaturized solar cells. They’re well suited for applications with sufficient illumination (indoor or outdoor) and often used for sensor applications such as temperature, humidity, illumination or CO2 sensors. Energy delivery can be scaled by adjusting the solar cell’s size based on the available space set by the application.
Temperature differences can generate energy based on Peltier elements. The standard application for these elements is to cool an area (e.g. cooling box) when electrical energy is applied. The reverse effect, generating energy based on temperature differences, is used for thermal harvesting. The output voltage of Peltier elements depends on the temperature difference and is typically very small (e.g. 20 mV for 35.6°F temperature difference). Specialized electronics is therefore required to use this energy.
The payload associated with sensors is often small (a few bytes). Therefore, an optimized protocol must limit the transmission overhead (frame control, preamble, synchronization, error checking) as much as possible while maintaining highly reliable communication.
Standard IP protocol (UDP over IPv6) requires more than 50 bytes of overhead. Hence, native IPv6 communication usually isn’t possible in energy harvesting sensor applications. The power optimized ISO/IEC 14543-3-1X protocol in contrast requires only 12 bytes in total to transmit 1 byte of sensor data. Using such protocol in conjunction with an intelligent transmission strategy (e.g. transmission of significant changes only) enables even use of redundant sub-telegrams to increase transmission reliability.
Energy harvesting wireless sensors must be in an ultra-low power sleep state for more than 99.99% of the time. Minimizing power consumption in this state is therefore essential. For example, the total budget of 300 nA needs to cover processor consumption in sleep mode (with the ability for timer-based periodic wake-up) as well as losses due to leakage in the energy store. Such low power consumption levels are difficult to achieve even with the latest processors and are the biggest design challenge. Custom mixed signal designs coupled with optimized system architecture is required to address these challenges.
Today, input data for the IoT is often provided by wired sensors that are locally connected to controllers and actuators. Here, all network components are in close proximity and directly connected with each other. This approach is well suited to local applications with limited flexibility needs where data reuse isn’t required. In many cases, an IoT network doesn’t require such proximity as it allows for centralized or cloud-based data processing. Thus, the same data can be used for several applications, driving down infrastructure cost and allowing dynamic network structures.
These characteristics require a second cloud, consisting of sensor and actuator nodes that can be deployed and expanded flexibly. Nodes that use minimal energy, which they harvest from their surroundings, provide a “fit and forget” solution, installed in inaccessible locations and relied on to execute their task with minimal maintenance or attention.