From bus stop signs to complex, networked industrial systems, the way most electronic systems are designed has been dramatically changed by the internet. Perhaps the biggest change is the introduction of sensor systems that collect data and transmit information to the cloud.
These small “devices” typically cannot be connected to a mains power source, meaning they must be powered by batteries or energy harvesting devices.
For many applications, energy harvesting devices are the most viable solution. If the device is designed with low power consumption and the energy harvesting device can harvest a large amount of energy, the device may be able to operate indefinitely.
However, this method is not suitable for many applications due to limited energy availability or excessive system energy requirements. In such cases, batteries are needed to power the system.
Unfortunately, batteries need to be replaced frequently, and the cost of replacing batteries often exceeds the cost of the IoT device itself. Therefore, estimating battery life is crucial.
Factors affecting battery life
Battery life of IoT devices can be determined through a simple calculation: battery capacity divided by the average discharge rate. Minimizing the energy used by the device or increasing battery capacity will increase battery life and reduce the total cost of ownership of the product.
Batteries are typically the largest component of IoT sensor systems, and engineers have limited options. However, by employing a wide range of processors, communication technologies, and software algorithms, systems can be designed to achieve the desired lifespan.
IoT processor sleep mode
The processor, designed for IoT applications, offers a variety of ultra-low power sleep modes.
Taking the TICC2650MODA wireless microcontroller as an example, Figure 1 shows the current consumption of the device in different operating states. There are six power consumption levels from power off to active operation.
Unless the data sampling frequency is extremely low, shutting down the processor offers little benefit. Furthermore, it requires additional circuitry and code to restart the processor, unnecessarily increasing cost and complexity. In addition, standby mode consumes less than 3μA of current, and a battery discharge time of at least eight years—longer than the lifespan of many IoT devices and almost reaching the shelf life of a CR2032 battery. Therefore, completely shutting down the processor is often counterproductive.
Choosing the appropriate standby mode is important. The lowest power standby mode consumes about one-third of the current of the highest power mode, but saves very little processor space. While some IoT applications require the lowest power sleep mode, most applications will choose to retain cache to reduce the cycles required to process active modes.
Processing workloads in active mode need to be balanced. Figure 1 shows that due to the CMOS technology used in this type of IoT processor, power consumption increases linearly with clock frequency. Therefore, a faster clock speed would seem to mean shorter battery life. However, since the "basic" current is 1.45mA , running the same algorithm at a faster clock speed requires a shorter wake-up time, meaning that slowing down the clock is not worthwhile and actually shortens battery life.
Furthermore, the wake-up time for switching from one mode to another is also limited: for example, the CC2650MODA requires 151μs to switch from standby to active mode. At its maximum clock frequency of 48MHz, this requires over 7000 clock cycles of power to wake the processor. For applications that require only a small amount of code, slowing down the clock during wake-up to allow for longer code execution time and reduce power consumption can extend battery life. Similarly, minimizing wake-up operations and performing as many tasks as possible before returning to standby mode can also extend battery life.
Modern IoT devices are highly complex products, integrating numerous peripherals, enabling single-chip solutions to meet diverse needs. However, IoT devices—especially simple sensors—often do not require these complex functionalities.
Figure 2 shows the power consumption of the available peripherals in the TICC2650MODA series. Although the current consumed by each device is very small—only tens or hundreds of microamps—disabling these devices can have a significant impact. A total of 318 μA can be saved if the serial connection is not needed. While this may not seem like much, this current change can have a significant impact on battery life.
Internet of Things (IoT) communication technology
The choice of the right communication technology usually depends on system requirements. Battery-powered IoT systems often require the use of radio frequency (RF) links.
In wireless communication, greater range or faster data transmission rates usually require more energy, so the lowest power communication technology that meets these needs is usually the wise choice.
For IoT sensors, there are currently several mainstream technologies. For example, LoRa technology can build a low-power, long-range wide area network (WAN) covering a range of several kilometers, while Bluetooth Low Energy (BLE) technology can only communicate over short distances, but consumes significantly less power. Another crucial decision is whether to use an on-chip device or choose a separate chip for communication.
Communication interface management is critical because even low-power communication technologies can quickly drain batteries, and the processing requirements are typically higher than those of the radio frequency stage.
In order to make the most of the communication battery capacity, many IoT systems only wake up the communication circuit when enough data has been accumulated to warrant transmission.
Select sensors to maximize battery life.
Sensors can significantly impact the battery life of IoT systems. For example, resistance temperature detectors and thermistors change their resistance with temperature. Simple applications requiring low accuracy can use voltage dividers, but high-precision systems require a current source, which demands more power. For many applications, an integrated temperature sensor such as the TILM35DZ is an excellent solution: this device is accurate to ± 0.25 °C at room temperature and consumes only 60μA. Regardless of the sensor chosen, it is essential to ensure that power is only drawn from it when it is in use.
Battery technology for the Internet of Things
One problem with battery selection is that many batteries have very limited specifications. Aside from physical size and output voltage, the only other parameter often specified is capacity. Battery capacity is clearly critical because it determines the total amount of electricity available to IoT devices.
Battery quality has a significant impact on capacity. Simply designating a particular model could risk purchasing a low-capacity, inexpensive device. This, in turn, would shorten battery life in IoT applications and lead to expensive battery replacements. Furthermore, batteries composed of different chemical substances may be used: different chemical compositions can have a substantial impact on battery life.
Many battery datasheets easily lead one to believe that batteries are very simple devices with a fixed capacity, but this is not the case. For example, if the load requires a higher current, the battery life will be significantly shortened. More importantly, for some applications, the battery capacity will decrease considerably as the temperature drops.
IoT applications utilize pulsed current. Processors and sensors can draw short pulses of current, a few milliamps, then switch to a low-power mode and maintain it for an extended period. Using pulsed current causes a drop in output voltage. Figure 3 shows that even a 2mA pulsed load causes the CR2032's output to drop from 3V to approximately 2.2V .
Engineers often prioritize battery capacity storage over energy consumption. However, IoT applications typically require operation for years on a single battery, making shelf life crucial. Most batteries only offer a seven- to eight-year shelf life.
Conclusion: Maximize battery life
Developing battery-powered IoT devices requires rigorous engineering design. While component selection is important, poor design can undermine the advantages of low-power processors. The key to extending battery life is ensuring the processor remains in low-power standby mode as much as possible and minimizing the use of wireless communication.
Against this backdrop, element14 has developed a calculator to help users quickly and easily predict the battery life of IoT systems (Figure 4). Users simply need to input relevant parameters of their processor, communication devices, sensors, and batteries, along with key details of the software operation, and the calculator can predict the battery life of IoT devices.
For more information, please visit the Power Electronics channel.
