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Push the Limit of Your IoT Device’s Battery Life

2021-03-16  |  7 min read 

The prolonged period of pandemic and the need for social distancing is presenting an opportunity to extend the automated solution into a range of industries. Smart retail could be one example. New IoT applications are now focused on using sensors to monitor and control physical things. Sensors, electronics systems, and smart devices are sending data to each other, capturing, analyzing data, and sending it to the cloud for storage or further processing. On top of that, there, there is an increased interest in artificial intelligence processing at the edge, making a smart device even smarter. The growing need for applications and data processing on smart devices has created a challenge for device designers: how to get more out of the battery.

Battery life is a key concern when designing portable IoT devices. Device designers need to identify the critical events that contribute to power consumption and how frequently those events happen. They also need to make design changes or tradeoffs to optimize battery life.  Design engineers will always find ways to conserve energy — balancing active functions and deep sleep mode. However, there is a baseline of power consumed by a certain part of the circuitry that needs to be on at all times. One example would be a pacemaker. A certain part of the circuitry will need to be always on for continuous monitoring, limiting the battery life.

Fortunately, many techniques are available to make electronic circuitry more power-efficient, helping to extend the battery life of the device. Here are a few examples.

Energy harvesting is an example of how one can prolong battery life (or maybe even eliminate it altogether!). It is a method of collecting energy from the environment and converting it to useful energy that can power electronic circuitry. For example, RF energy harvesting captures ambient electromagnetic energy and converts it into a usable continuous voltage (DC), with an antenna and a rectifier circuit. The presence of ambient RF energy in the environment results from numerous high-frequency technologies, including Wi-Fi signals, microwave ovens, and radio broadcasting. Other energy harvesting methods include thermoelectric conversion, solar energy conversion, wind energy conversion, and vibrational excitation. Today, several companies are creating energy harvesting chips that eliminate the need for battery replacements for low-power IoT devices — here is an example.

Wireless connectivity standards, cellular and noncellular, have developed features and optimization techniques to help maximize IoT device battery life. Wireless standards such as LTE-M and 802.11 wireless LANs have features such as power save mode (PSM) and extended discontinuous reception (eDRX) to lower power consumption.

PSM allows the IoT device to be in a sleep or “dozing” state at a fixed time, waking up only to transmit and monitor data before going back to sleep, all the while remaining registered with the network. The device and the network negotiate and optimize the timing based on the application’s requirements. Since the IoT device is inactive during PSM mode, power consumption is lower, helping prolong the battery life.

eDRX can be incorporated into IoT devices as an extended LTE feature, working independently of PSM to obtain additional power savings. eDRX greatly extends the time interval during which an IoT device is not listening to the network. While not providing the same level of power reduction as PSM, eDRX may be a good compromise between device reachability and power consumption.

Power-efficient circuitry. Device designers strive to design electronic circuitry that is power-efficient. A certain hardware design, software, or firmware changes can cause the circuitry to draw more power.  Different climatic conditions can also cause power consumption to vary. Device designers often analyze how an IoT device consumes power in different scenarios by capturing and breaking power consumption down to hardware subsystems.

Take for example the air quality monitoring sensor that uses LPWAN technology. Device designers need to optimize the sensor’s design to ensure that the coin cell battery lasts for at least 10 years. They need to spend a lot of time testing many different real-life scenarios and correlating the events to the current consumption of the product, down to subsystem level — which is incredibly frustrating. On top of that, these steps must be repeated to analyze and verify the effects of each design change. This process is known as event-based power consumption analysis. Designers need to correlate the charge consumption profile to the RF or DC event of a subsystem. As described, the process to optimize device design can be difficult and time-consuming.

The KS833A2A event-based power analysis software, powering the X8712A IoT device battery life optimization solution, is an easy-to-use visualization tool to effectively capture and display the charge consumption profile at the subsystem level as your IoT device transitions through various operating states. It then estimates the battery life of your device based on the profile, helping you to identify the contribution of these subsystems to the current draw.

Most people can relate to the anxiety caused by a low mobile phone battery. IoT devices are no different, be it a smartwatch, a medical device, or a smart sensor for agriculture applications. Battery runtime is one of the most essential criteria which influences the end-users buying decision. It can give your IoT device a competitive edge or destroy your brand’s reputation. Fortunately, available technology and solutions can help product makers and device designers make informed decisions to manage power efficiently and optimize their IoT device’s battery life.