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Chip Solutions Tackle the Energy Harvesting Challenge

Written by Jeff Child

Self-Sufficiency at the IoT Edge

While many IoT edge devices often need to be extremely low power, having an ability to harvest their own power is an even better scenario. Chip solutions continue to emerge aimed at the energy harvesting challenge.

Forecasts predict that there’s likely to be a trillion IoT sensor nodes deployed in the world by 2025. Powering those devices is going to be a challenge because many of those will be low power modules residing in remote areas. Energy harvesting will be critical in those applications because it just won’t be practical to replace trillions of batteries that only last a year or two.

To help you meet that challenge, there’s a variety of chip and development platform solutions available that attack various parts of the energy harvesting puzzle. These include specialized microcontrollers (MCUs), power management chips, power regulator ICs as well as complete platform solutions and reference designs—all aimed at energy harvesting.

The three most popular types of energy harvesting are solar, piezoelectric (vibration/rotation) and thermoelectric. Of the three, solar is the most widely used today and it relies on photovoltaic cells to provide energy. It’s the best fit for typical smart home, smart agriculture, smart industrial and similar applications. Piezoelectric energy harvesting leverages vibration/rotation types of energy, and is practical if you’re monitoring motors, generators or turbines—anything that moves or vibrates. Finally, thermoelectric energy harvesting is great for systems involving pipes—such as gas pipes or water pipes—where one side is hot and one side is cold, and energy can be harvested from heat transfer.

No matter what the power source, a module powered by energy harvesting relies on either a harvesting power supply or an alternative set of external components that converts input from a solar, piezoelectric or thermoelectric source into some voltage range and current. Some devices even accept multiple types of power source interfaces. But the key issue is that the system has to be efficient enough to be viable for the situation.

Local Edge Processing
For its part, Eta Compute’s approach to the energy harvesting challenge is to provide high performance local edge processing at low power levels. The idea is that it’s the RF communication portion of an IoT edge device that’s the most power hungry. If you can limit the amount of data communication needed, then you can more easily achieve a solution that can run off an energy harvesting power source.

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To illustrate the point, Eta Compute’s Chet Jewan cites an example of a low power image detection module designed to detect cars in your driveway. A module without much intelligence would only be able to send a full image or video data of the driveway, consuming a lot of power by the RF transmitter. But with sophisticated local processing, the module could decide whether to send an image of a car, or just a simple text saying whether a car is present or not. Moreover, the local processing could even decide to take some local action itself, requiring no RF data transmission at all. “A high level of local processing can sense, infer and act locally,” says Jewan.

Eta Compute’s flagship product is its ECM3531 ASIC chip for machine learning algorithms based on the Arm Cortex-M3 and NXP Coolflux DSP processors. The SoC includes an analog-to-digital converter (ADC) sensor interface and highly efficient PMIC circuits. The chip also includes I2C, I2S, GPIOs, RTC, PWM, POR, BOD, SRAM and flash.

The ECM3551 has a dual-core architecture based on the M3 and Coolflux DSP that is designed for low power edge AI IoT applications (Figure 1). The device makes use of the company’s patented delay insensitive asynchronous logic (DIAL), which enables dynamic voltage frequency scaling and near threshold voltage operation. The MCU uses an Arm Cortex-M3 processor and operates below 1 MHz to over 100 MHz with power consumption as low as 4.5 μA/MHz. By using asynchronous processing of all digital logic, the architecture enables rapid interrupt response for low latency applications.

Figure 1 – The ECM3551 chip has a dual-core architecture based on the M3 and Coolflux DSP that is designed for low power edge AI IoT applications. The device makes use of Eta Compute’s patented delay insensitive asynchronous logic (DIAL), which enables dynamic voltage frequency scaling and near threshold voltage operation.

SOTB Technology
Renesas Electronics has approached the challenge of meeting extreme low power demands by applying innovations in semiconductor process development. A year ago, the company unveiled an innovative energy-harvesting embedded controller that can eliminate the need to use or replace batteries in a device. The R7F0E embedded controller—Renesas’ first commercial product using SOTB (silicon on thin buried oxide) technology—is a 32-bit, Arm Cortex-based embedded controller. The device is capable of operating up to 64 MHz for rapid local processing of sensor data and execution of complex analysis and control functions. The R7F0E consumes just 20 μA/MHz active current, and only 150 nA deep standby current, approximately one-tenth that of conventional low-power MCUs.

The extreme low current levels of the SOTB-based embedded controller enables system designers to completely eliminate the need for batteries in some of their products through harvesting ambient energy sources such as light, vibration and flow (Figure 2). Although the solution was developed with IoT devices in mind, the controller is more broadly aimed at what they call the new market of maintenance-free, connected IoT sensing devices with endpoint intelligence. This includes health and fitness apparel, shoes, wearables, smart watches and drones.

Figure 2 – The extreme low current levels of the SOTB-based embedded controller enables system designers to completely eliminate the need for batteries in some of their products through harvesting ambient energy sources such as light, vibration and flow.

In June of this year, Renesas followed up with the development of new low-power technology for use in embedded flash memory based on a 65 nm SOTB process. Available with 1.5 MB capacity, it is the first embedded 2T-MONOS (2 transistors-metal oxide nitride oxide silicon) flash memory based on 65 nm SOTB technology.

BLE Sensor Platform
As mentioned earlier, solar power is the most popular form energy harvesting used today. There are a growing number of IoT sensor applications where the duty cycle is low enough to support intermittent communications, allowing the energy needed to support operation to be harvested using renewable sources such as solar. Applications are expected to include smart home and building automation such as HVAC control, window/door sensors and air quality monitoring. Asset tracking including package open/close detection, shock monitoring, and temperature and humidity data logging are also possible applications.

Offering a complete platform solution, in May, ON Semiconductor introduced its RSL10 Multi-Sensor Platform powered only with a solar cell. This complete solution supports the development of IoT sensors using continuous solar energy harvesting to gather and communicate data through Bluetooth Low Energy (BLE), without the need for batteries or other forms of non-renewable energy.

The combination of ultra-low-power wireless communications, small form-factor solar cell and low duty cycle sensing applications makes it possible to develop and deploy totally maintenance-free IoT sensor nodes. The RSL10 Solar Cell Multi-Sensor Platform is enabled by the RSL10 SIP, a complete System-in-Package (SiP) solution featuring the RSL10 radio, integrated antenna and all passive components.

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The platform combines the RSL10 SIP with a solar cell and a host of low power sensors from Bosch Sensortec, including the BME280 all-in-one environmental sensor (pressure, temperature, humidity) and the BMA400 ultra-low-power 3-axis accelerometer (Figure 3). Together, they enable developers and manufacturers to create complete IoT nodes that are entirely powered through renewable energy or energy harvested from the sensor’s surroundings. For easy development, the platform is supplied with all design files (Gerber, schematic and BoM) and customizable source code as part of a CMSIS software package.

Figure 3 – The RSL10 Solar Cell Multi-Sensor Platform includes the RSL10 SIP, a solar cell and a host of low power sensors from Bosch Sensortec, including the BME280 all-in-one environmental sensor (pressure, temperature, humidity) and the BMA400 ultra-low-power 3-axis accelerometer.

High-Efficiency Battery Charger
Energy efficiency can make or break an energy harvesting implementation. Offering a battery charging solution, STMicroelectronics provides its SPV1050 chip, an ultralow power and high-efficiency energy harvester and battery charger, which implements the MPPT (maximum power point tracking) function and integrates the switching elements of a buck-boost converter. MPPT is a common function used in solar electric charge controllers.

The SPV1050 device allows the charge of any battery, including the thin film batteries, by tightly monitoring the end-of-charge and the minimum battery voltage in order to avoid the over-discharge and to preserve the battery life (Figure 4). The power manager is suitable for both PV cells and TEG harvesting sources, because it covers the input voltage range from 75 mV up to 18 V and guarantees high efficiency in both buck-boost and boost configurations.

Figure 4 – The SPV1050 device allows the charge of any battery, including the thin film batteries, by tightly monitoring the end-of-charge and the minimum battery voltage in order to avoid the over-discharge and to preserve the battery life. The power manager is suitable for both PV cells and TEG harvesting sources.

Meanwhile, the SPV1050 device boasts very high flexibility thanks also to the trimming capability of the end-of-charge and undervoltage protection voltages. That enables any source and battery to be matched. The MPPT is programmable by a resistor input divider and allows maximizing the source power under any temperature and irradiance condition.

An unregulated voltage output is available (for example, to supply an MCU), while two fully independent LDOs are embedded for powering sensors and RF transceivers. Both LDOs (1.8 V and 3.3 V) can be independently enabled through two dedicated pins.

Thermal-Based PMIC
Among the latest energy harvesting solutions from E-peas is its latest power management IC (PMIC) announced in February. The device is specifically optimized for energy harvesting from thermal sources in wireless sensor applications. Supplied in a space-saving 28-pin QFN package, the AEM20940 is a highly advanced device based on proprietary technology that is capable of extracting available input current up to levels of 110 mA.

Taking DC power from a connected thermal electric generator (TEG), it can supervise the storing of energy in a rechargeable element and simultaneously supply energy to the system via 2 different regulated voltages. This is done through its built-in low noise, high stability 1.2/1.8 V and 2.5/3.3 V LDO voltage regulators. The lower voltage can be employed for driving the system MCU, while the higher voltage is intended for the RF transceiver.

Through the AEM20940’s deployment, it will be possible to extend the system battery life or, in many cases, eliminate the primary power source from the system completely. In this way any dependence on having to regularly replace batteries (which often has serious logistical challenges associated with it, as well as adding to the overall expense) can be removed.

In more recent news from E-peas, in April, the company confirmed that its AEM10941 devices for photovoltaic energy harvesting are being incorporated into tracking equipment employed in Australian cattle ranches. E-peas engineers worked in conjunction with the team at Dutch systems integrator SODAQ on the development and implementation of energy efficient livestock monitoring hardware for Brisbane-based client mOOvement.

Through use of mOOvement’s smart tracker, valuable data on cattle herds can be acquired concerning their position and grazing patterns, with the ability to set alarms if individual animals are not moving or fenced boundaries have been breached (Figure 5). Attached to one of the cattle’s ears, each tracker comprises an accelerometer, a LoRa communication module (with built-in MCU) and a GPS transceiver, as well as a passive NFC tag.

Figure 5 – A key design requirement of the mOOvement smart tracker project was that the size and weight of the unit had to be kept as low as possible, in order to minimize the impact on the animal. This placed severe restrictions on the surface of the solar panel that could be accommodated.

A key design requirement of the project was that the size and weight of the unit had to be kept as low as possible, in order to minimize the impact on the animal. This placed severe restrictions on the surface of the solar panel that could be accommodated (with it measuring slightly less than 19 mm x 43 mm in total and capable of generating 0.125 W). Consequently, the power system needed to be ultra-efficient.

Cold Start-Up PMU
IoT devices relying on energy harvesting in low energy conditions often have to slowly accumulate enough energy to turn on, resulting in long delays before the device can start sensing, processing and transmitting. This can result in missed data collection, slow operation and poor user experience. With that in mind, Analog Devices provides its ADP509x power management unit (PMU) that’s designed to solve these problems with a multiple-power-path design, which enables faster startups and smoother operation.

ADI says that a key barrier for energy harvesting is that in many applications energy from the environment is only available at very low levels (for example, low-light indoor solar harvesting), and periodically not at all. This requires power management solutions that can not only enable satisfactory system operation with very little energy, but also efficiently manage energy storage devices to satisfy energy demand at times when no energy is being harvested.

Due to its unique circuit design, ADI claims the ADP509x as among the most efficient energy harvesting PMUs on the market, converting harvested power down to the 16 μW to 100 mW range with only sub-μW operation losses. The ADP509x also delivers the fastest cold-startup time available, according to ADI.

Boost/Buck Converter
Among the solutions for energy harvesting from Texas Instruments (TI) is its bq25570 chip, a nano power boost charger and buck converter for energy harvester powered applications.

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The bq25570 device is specifically designed to efficiently extract microwatts (µW) to milliwatts (mW) of power generated from a variety of high output impedance DC sources like photovoltaic (solar) or thermal electric generators (TEG) without collapsing those sources.

The battery management features ensure that a rechargeable battery is not overcharged by this extracted power, with voltage boosted, or depleted beyond safe limits by a system load. In addition to the highly efficient boosting charger, the bq25570 integrates a highly efficient, nano- power buck converter for providing a second power rail to systems such as wireless sensor networks (WSN), which have stringent power and operational demands. All the capabilities of bq25570 are packed into a small foot-print 20-lead 3.5 mm x 3.5-mm QFN package (RGR).

TI also offers a reference design based on the bq25570. The TIDA-00242 reference design is a solar charger and energy harvester, using a highly integrated power management solution that is well-suited for ultra-low power applications (Figure 6). The product is specifically designed to efficiently acquire and manage the microwatts to milliwatts needed to power your design. The storage method is a 47 nF super capacitor that is charged and maintained by 4 series low power solar elements using MPPT.

Figure 6 – The TIDA-00242 reference design supports MPPT to provide optimal energy extraction from solar panels. It also has internal battery charging and protection circuits. It makes use of the buck and boost capabilities of the bq25570 chip.

The TIDA-00242 reference design supports MPPT to provide optimal energy extraction from solar panels. It also has internal battery charging and protection circuits. It makes use of the buck and boost capabilities of the bq25570. Input voltage regulation prevents collapsing high impedance input sources (boost). And support is provided for programmable step-down regulated output (buck). Energy is stored in a super capacitor, for use in low power applications. The reference design is a complete solution, including the solar current source, charge management solution, super cap and a built-in LDO regulator.

RF Energy Harvesting
While one viewpoint is that RF communication is major power problem for energy harvesting applications, start-up Wiliot takes an entirely different approach. Wiliot’s technology seeks to harvest energy from the RF transmissions themselves. According to the company, there are two approaches to harvesting RF energy: RF scavenging and intentional RF energy transfer. The first mode of operation taps into existing sources of energy from devices being used without the intention of generating energy, the energy available over-the-air is intermittent and unpredictable. The resulting applications this mode can enable are stochastic in nature.

Wiliot says that in the latter approach, the source of energy is deterministic in terms of power levels and time, with a specific duty cycle pattern delivered from an infrastructure planned to provide it. As such the resulting energy output is also more predictable, and the transmission of packets from radio powered are transmitted at a predictable cadence.

Wiliot uses RF harvesting techniques to power its chip, consisting of a Bluetooth radio, the Arm Cortex M0+ core, a set of sensors and a security element (Figure 7). It can work in both modes of operations, though the one it’s designed for is the first. When considering the increase in the background interaction of products and consumer devices that are battery-powered like smartphones, the prospect of harvesting power without the need for infrastructure is attractive.

Figure 7 – Wiliot uses RF harvesting techniques to power its chip, consisting of a Bluetooth radio, the Arm Cortex M0+ core, a set of sensors and a security element.

Technology Release Plan
In August, Wiliot announced an update on its release plan for its technology. So far this year, Wiliot has designed and built 5 prototype chips. With each version, the company has increased robustness, and also added encryption, multiple on-chip sensing capabilities, and harvesting from three radio bands simultaneously. Its most recent milestone was the completion of the first production chip design, a “release candidate,” which should power the Version 1.0 Wiliot tag and move them from making small batches of product to volume production.

The rest of this year will be focused on taking this release candidate chip from wafer, through processing, testing, configuration, all the way to conversion into the final tag form factor, ready for the first field tests next year. By the end of 2019, Wiliot expects to have a good sense of the performance of the release candidate. In Q2 2020, it plans to roll out some of the existing Early Advantage Program projects its been working on this year. During 2020, the company will continue a controlled release of that product.

Clearly, the stakes are high for future development of energy harvesting technology. As designers of IoT edge modules strive for lower power operation, energy harvesting solutions expand the conditions in which that can operate. The battery-free advantages of energy harvesting will open up new areas of IoT implementations that would otherwise not be practical. Chips developers will continue to address that challenge with a variety of energy harvesting solutions. 

For detailed article references and additional resources go to:
www.circuitcellar.com/article-materials

RESOURCES
Analog Devices | www.analog.com
E-peas | www.e-peas.com
Eta Compute | www.etacompute.com
Renesas Electronics America | www.renesas.com
ON Semiconductor | www.onsemi.com
STMicroelectronics | www.st.com
Texas Instruments | www.ti.com
Wiliot | www.wiliot.com

PUBLISHED IN CIRCUIT CELLAR MAGAZINE• NOVEMBER 2019 #352 – Get a PDF of the issue


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Editor-in-Chief at Circuit Cellar | Website | + posts

Jeff Child has more than 28 years of experience in the technology magazine business—including editing and writing technical content, and engaging in all aspects of magazine leadership and production. He joined the Circuit Cellar after serving as Editor-in-Chief of COTS Journal for over 10 years. Over his career Jeff held senior editorial positions at several of leading electronic engineering publications, including EE Times and Electronic Design and RTC Magazine. Before entering the world of technology journalism, Jeff worked as a design engineer in the data acquisition market.