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Cover Story pages 4–7 : Würth Elektronik share their expertise on Aluminium capacitors: Aluminum Electrolytic vs. Aluminum Polymer Capacitor and how its benefits are used properly

Pages 8-10: Matthias Kassner, En-Ocean and Ankur Tomar, Farnell ele-ment14 explain in great details why Energy-Harvesting Wireless Sensor Nodes are the Key to the Internet of Things

Pages 11-12: Tony Armstrong, and Dave Salerno, Power by Linear Products, Analog Devices tell us how Energy Harvesting From Ther-moelectric Sources Gets a Boost From an Ultra-low Voltage Converter

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Contents

Dear readers,

This is the second issue of eeNews Embedded a quarterly publication that has deep roots in thepanEuropean publishing industry, going as far as Embedded Systems Europe. The publication isedited by a team composed of Ally Winning and Wisse Hettinga who together have a wealth ofexperience in the Embedded field.

The editorial focus is on Embedded hardware and software including RTOS dedicated to avionicsand automotive and development tools. The editorial mix also includes IoT (Internet of Things)Industrial IoT, smart power, medical electronics as well as electronics modules and board level computers.

eeNews Embedded ‘s web site www.eeNewsEmbedded.com is a central point for thecommunity of Embedded design engineers in Europe looking for Embedded design, software,Development tools and product information. The site also enjoys Wisse’s famous comicscharacters Hmm and Aha whose discussions can be followed on the site. ( see bottom of page)

André RousselotPublisher

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Pages 13-14: Mark Patrick, Mouser Electronics Europe discuuses how Accessible heart monitoring solu-tions point to preventative mainte-nance for people

Pages 16-17: Steven Dean, ON Semiconductor has been Listening to the market: this article highlights the emergence of Over-The-Counter (OTC) hearing aids which has been made possible by new silicon

Pages 18-19: HD Lee, CTO, Per-vasive Displays details how IoT displays can be implemented in applications where data rates and power consumption are restricted

HMM and AHA discuss Ohm’s law in space

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Aluminum Electrolytic vs. Aluminum Polymer Capacitor and how its benefits are used properlyFrank Puhane

Understanding Polymer Electrolytic Capacitors Aluminum polymer capacitor (also called polymer electrolytic capacitors or in short polymer e-caps) is a sub-form of the electrolytic capacitors. The special feature of these capacitor types is that a conductive polymer is used instead of a liquid electrolyte. This requires a special processing step, which is carried out during production. In this chemical reaction, the so-called polymerization, by heating, the still liquid monomer that has been impregnated in place of electrolyte in the separator paper is cross-linked to a solid polymer. This process is typically done at a temperature of about 100 °C. Once completed, the polymer is solidified indefinitely. The various combinations that are possible today for electrolytic capacitors fabrication in terms of electrodes and the property of the electrolyte are shown in Figure 1.

Furthermore, there is the possibility of hybrid construction of electrolytic capacitors. This is a combination of wet electrolyte and solid polymer. Aluminum electrolytic and aluminium poly-mer capacitors have very good behaviour against bias effects of voltage and temperature. Furthermore, aluminium polymer capacitors have very good aging characteristics. In compari-son to ceramic capacitors, polymer electrolytic capacitors offer significant advantages, especially their DC bias performance. In addition, the use of polymer capacitors becomes interesting when increasing the capacitance while maintaining cost. The special design process can also be used to significantly reduce the parasitic effects (here especially the ESL). This means for applications the potential to handle high ripple current, have low parasitic inductances, high reliability and very good tempera-ture properties. The equivalent circuit of a capacitor is shown in Figure 2. It should be noted that polymer electrolytic capacitors have an increased leakage current compared to normal alumi-num electrolytic capacitors and therefore are usually unsuitable for small handheld battery applications.

The high reliability is proven by the significantly longer life-time of polymer electrolytic capacitors. However, when it comes to high vibration, the specific circumstances of the application should be considered, as aluminum polymer capacitors may not be the optimal choice here. This is due to the property of the solid polymer because it cannot absorb vibrations as well

as a liquid electrolyte. However, it has to be considered that in terms of volume for a defined capacity and voltage, the normal electrolytic capacitor still has advantages. At Würth Elektronik eiSos, for aluminium polymer capacitors the capacitance values range from 10 μF to 2 mF with a voltage range from 6.3 V to 100 V in a wide variety of designs. Due to their excellent electrical properties, the possibilities of using polymer electrolytic capaci-tors are very diverse, ranging from traditional backup solutions of voltages, buffering supply voltages from ICs, bypass or decoupling of signals, filter applications to voltage smoothing of switching regulator applications. This Application Note dis-cusses the use of aluminum polymer capacitors in the field of filtering and voltage smoothing.

The Buck Converter - General SetupTo demonstrate the positive effects of the polymer electrolytic capacitor a buck converter is used. The input voltage is 12 V and the output voltage has been set to 5 V. The load is a pure ohm load of 5 Ω. This results to a current of 1 A flowing through the resistor. This setup serves as a basis to make the perfor-mance of polymer electrolytic capacitors clear. The design is used for both EMC measurement and voltage ripple output measurements with always the same load. From the EMC point of view, a buck converter is much more critical at the input side. This is due to the discontinuous current consumption based on the fast switching processes of the semiconductors. As a result of this topology, there is already an “LC filter” at the output, which integrates the discontinuous current on the high side (refer to Figure 3).

The construction and design of the buck converter was based on the specifications of the data sheet and designed with the default values for the coil and capacitors. The inductance values of the coil and the capacitance of the input and output capacitors were verified by the manufacturer’s data sheet and with their simulation software. This was especially important when using only one aluminum electrolytic capacitor. Due to the very high ESR value, the stability of the regulator was impaired. To counteract this effect, a capacitor was additionally attached to the feedback loop. This additional capacity ensures stability even at high ESR values. In Figure 4 the circuit diagram of the buck converter and in Figure 5 the associated layout is shown.

The layout consists of two layers, each with full copper areas on the top and bottom sides with connection to ground. The layout itself could still be improved at various points. Above all, the connection of the components to the ground layer still

Cover story

Aluminum Tantalum Nioboium Non-solid /

wet Solid /

dry Non-solid /

wet Solid /

dry Non-solid /

wet Solid /

dry

Figure 1: Construction possibilities of electrolytic capacitors

Figure 2: Equivalent circuit diagram of a real capacitor

Figure 3: Principle of a buck converter

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needs optimization to achieve a better filtering effect. It can clearly be seen in the measurement of the output capacitor that the high parasitic inductance causes voltage peaks on the output signal.

The EMC measurement The measurements were made according to the CISPR 32 standard (which replaces CISPR 22 and 15) in an RF-shielded chamber with the corresponding connection to the ground surface of the cabin, see Figure 6. The test receiver was an R&S ESRP 3 and as network simulation an ENV216 two-wire V-net simulation was available.

During the measurement, in the first step, further input filters on the layout were dispensed; only in the last measurement was a T-filter with a separated coil placed. This filter was construct-ed according to the specifications in the data sheet.

For the first measurement, an aluminum electrolytic capacitor WCAP-ASLL 865 060 343 004 was used for the input capaci-tor C1 (Link to REDEXPERT). The electrical properties of the capacitor are as follows: Capacitance 47 μF, rated voltage 16 V with an ESR 411 mΩ and ESL 19 nH. The associated measure-ment result is shown in Figure 7

It can be seen that the limit values of CISPR 32 class B are clearly exceeded. There are noise levels of up to 100 dBμV de-tectable. But where do these interfering signals come from? The capacitor as a real component has parasitic effects, particularly the ESR together with the parasitic effects of the layout (the lead inductance) generate a high-frequency voltage drop that can be detected by measurement. This is shown schematically in Figure 8.

As a first approach to achieve acceptable levels of emissions and stay below the limits, an aluminum polymer capacitor can be used. The electrical properties in terms of capacity and rated voltage of the aluminium polymer capacitor are the same as those of the aluminum electrolytic capacitor. The design is also equivalent at the capacitance of 47 μF and the capacitor fits to the original landing pattern. The aluminum polymer capacitor used was a WCAP-PSLP 875 105 344 006 (Link to REDEX-PERT) with a capacitance of 47 μF, rated voltage of 16 V and with an ESR of 20.7 mΩ and ESL of 3.9 nH. Due to the very low ESR and ESL, the following measurement of the interference spectrum is achieved, which can be seen in Figure 9.

It can clearly be seen that by changing only one component, the EMC performance was significantly improved. The voltage drop which is generated by the fundamental frequency and the first harmonic of this frequency is reduced and thus less interference is generated. However, the limit could not be met and therefore further filters have to be placed. The structure of the input filter was based on the information in the data sheet.

Figure 4: Schematic of the buck converter

Figure 5: Layout of the buck converter

Figure 6: Setup of the EMC measurement according to CISPR 35

Figure 8: Schematic representation of the cause of the disturbances

Figure 7: First EMC measurement with an aluminum electrolytic capacitor as C1

Figure 9: EMC measurement with an aluminum polymer capacitor as input capacitor



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Cover story

Therefore, the filter has the following insertion loss (in a 50 Ω system), as shown in Figure 10

The input filter was then included on the PCB and another measurement performed. The result is shown in Figure 11 where the interaction between the aluminum polymer capacitor and the input filter is visible.

The combination of input filter and low ESR and low ESL polymer electrolytic capacitance makes it possible to push the level broadband below the limit of class B. Values of less than 40 dBμV (Average & Quasi Peak) are easily possible (compared to the first measurement with around 100 dBμV) and so, the measurement is passed.

Comparison of the ripple of the output signalFor the output capacitor of a buck converter, a certain capaci-tance is required in order to keep the control loop stable and hence the output voltage stable. If the output voltage reduces the capacitance value, the worst-case scenario is the converter can no longer meet its specification (for example during load changes). This must be taken into account, especially when op-erating with class 2 ceramic capacitor (e.g. X7R and X5R). In the following chapter, the effect of the resulting ripple on the output signal will be considered. The first measurement in Figure 12 shows the result of the output ripple of the switching regulator when only one aluminum electrolytic capacitor is used.

The capacitor used is a WCAP-ASLL 865 060 343 004, the same as used previously (REDEXPERT). The electrical proper-ties of the capacitor are as follows: Capacitance 47 μF, rated voltage 16 V with an ESR 411 mΩ and ESL 19 nH. The high ESR value results in a peak-to-peak value of 400 mV. At least, this means a voltage ripple of 8 % at an output voltage of 5 V. Even with two aluminum electrolytic capacitors of the same type in parallel, the resulting ESR is still 205.5 mΩ and thus clearly too high. Another aspect that should not be neglected is the ripple current through the capacitor. This leads to heat-ing of the component and leads to the failure of the capacitor. Therefore, the ripple current capability of aluminum electrolytic capacitors must always be checked. In the case of polymer electrolytic capacitors, due to the low ESR, the heating of the component at the same ripple current is significantly lower and, in comparison, therefore significantly larger ripple currents are capable without thermally overloading the component. A comparison of the ESR of the aluminum electrolytic capacitor and the ESR of the polymer electrolytic capacitor is as shown in Figure 13.

The measurement of the residual ripple of the output signal with the polymer capacitor as an output capacitor is shown in Figure 14. The aluminum polymer capacitor used was a WCAP-PSLP 875 105 344 006 (Link to REDEXPERT) with a capaci-tance of 47 μF, rated voltage of 16 V and with an ESR 20.7 mΩ and ESL 3.9 nH

The peak-to-peak value of the measurement is now only 50 mV and therefore within an acceptable range. The voltage peaks seen in Figure 14 are caused by parasitic inductance during the switching. Since, no one would use single aluminum polymer electrolytes alone in a real application; it is advisable to place an MLCC in parallel to the aluminum polymer capacitor. Thus, the parasitic effects can be minimized and a very clean output signal is achieved, as shown in Figure 15.

Figure 12: Residual ripple at the output of the buck converter if only one aluminum electrolytic capacitor is used

Figure 13: Comparison of the ESR of the aluminum and aluminum polymer capacitor

Figure14: Measurement of residual ripple when using the aluminum polymer capacitor at the output

Figure 10: Built-in input filter with shown filter performance

Figure 11: EMC measurement with input filter and aluminum polymer capacito



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The MLCC used was a X7R ceramic with a capacitance of 4.7 μF and rated voltage of 16 V (Link to REDEXPERT). If the layout of the PCB will be optimized too, a peak-to-peak value of 20 mV is expected, see also Figure 15.

Lifetime consideration The lifetime of electrolytic capacitors is very important in in-dustrial applications and other application where a high lifetime is required. Here, the capacitor is not used as a kind of prede-termined breaking point (also called planned obsolescence) as it is in consumer electronics but is as a durable and reliable component. The life of a capacitor depends on many factors of the application. An important factor is the temperature or rather thermal load, as it is responsible for the fact that internal struc-tures age over time and the electrical properties deteriorate. This results in increased leakage current, increasing the ESR, which in turn leads to a further increase of the temperature. The reason for the temperature increase is the power loss generated by the ESR. If these limits are not exceeded, high lifetime ex-pectancies are possible when the inner temperature load of the component is in a lower range. A comparison of the lifetime of aluminum electrolytic and aluminum polymer capacitors by tem-perature load is listed here. The bases of this consideration are two formulas. With liquid electrolytic capacitors, the expected lifetime doubles when the temperature at the component is reduced by 10 °C (2). For polymer electrolytic capacitors, the life increases tenfold when the temperature at the component is reduced by 20 °C (1).

Formula for aluminum polymer capacitors:

𝑳𝑳𝒙𝒙 = 𝑳𝑳𝒏𝒏𝒏𝒏𝒏𝒏 ∗ 𝟏𝟏𝟏𝟏𝑻𝑻𝟏𝟏+𝑻𝑻𝒂𝒂𝟐𝟐𝟏𝟏 (1)

Formula for aluminium electrolytic capacitors:

𝑳𝑳𝒙𝒙 = 𝑳𝑳𝒏𝒏𝒏𝒏𝒏𝒏 ∗ 𝟐𝟐𝑻𝑻𝟎𝟎+𝑻𝑻𝒂𝒂𝟏𝟏𝟎𝟎 (2)

To further illustrate this, the calculated lifetime values are shown in Table 1 for some example temperature values. Here, the maximum specified component temperature is used to compare aluminum electrolytic and aluminum polymer capaci-tors.

The table is divided into four columns. The application temperature is defined in the formulas (1) and (2) as the ambi-ent temperature Ta. The hour’s definition at 105 °C in the two following columns for the aluminum polymer and aluminum electrolytic capacitor is the nominal lifetime of the component Lnom. This is linked to the maximum specified temperature at the component and is defined as T0. The other hours in the table are the calculated lifetimes Lx using the formulas (1) and (2). The calculated factor in the last column is the relation be-

tween the calculated lifetime for aluminium electrolytic and alu-minium polymer capacitors. In the aluminum polymer capacitor column, the calculated lifetime is 2.000.000 h at 65 °C ambient temperature. This means a theoretical lifetime of 228 years. To guarantee such a lifetime is not possible. The typical maximum guaranteed lifetime varies for different vendor and is between 13 and 15 years.

Furthermore, you can clearly see in this table at which ambi-ent temperature aluminum polymer capacitors have their ad-vantage in lifetime. If the specified component temperature for aluminum electrolytic and aluminum polymer capacitors is the same (for example 2000 h at 105 °C), it can be seen at 95 °C the polymer electrolytic capacitor has a longer lifetime. Only in cases of aluminum electrolytic capacitors with a long specified lifetime at the maximum specified component temperature (for example 5000 h at 105 °C) has a higher intersection point but the point of intersection will always occur (see Figure 16). The specified hours in this diagram are always the nominal lifetime value of the component at this temperature. Apart from this advantage, of course, the other parameters of the capacitors must be compared. It may be that in a special application the expected lifetime is the same, but the better ESR and ESL are critical to the application and speaks for the aluminium polymer capacitor.

SummaryAluminum polymer capacitors, because of their construction, have significant advantages for electronic applications. Low ESR and low ESL values in addition to very high expected lifetime make this technology extremely interesting for many diverse applications. Therefore, the possible use should be considered based on the information provided in this Applica-tion Note. This can improve the behavior of the design and ultimately increase the performance of the application.

USEFUL LINKS

Application Notes www.we-online.com/app-notesREDEXPERT Design Platform www.we-online.com/redexpertToolbox www.we-online.com/toolboxProduct Catalogue www.we-online.com/products

CONTACT INFORMATION

[email protected] Tel. +49 7942 945 - 0

Würth Elektronik eiSos GmbH & Co. KG Max-Eyth-Str. 1 74638 Waldenburg Germanywww.we-online.com

Figure 15: Measurement of residual ripple using am aluminum polymer capacitor and an MLCC

Temperature Aluminum-Ploymer-Capacitor Aluminum-Electrolytic-Capacitor 125 °C 2.000 h 2.000 h 1.000 h 105 °C 20.000 h 2.000 h 8.000 h 4.000 h 2.000 h 1.000 h 85 °C 200.000 h 20.000 h 32.000 h 16.000 h 8.000 h 4.000 h 65 °C 2.000.000 h 200.000 h 128.000 h 64.000 h 32.000 h 16.000 h

Table 1: Lifetime overview with different ambient temperatures

Figure 16: Overview of the expected lifetime of aluminum and aluminum polymer capacitors



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Energy Harvesting

Energy Harvesting Wireless Sensor Nodes are the Key to the Internet of ThingsMatthias Kassner, EnOcean and Ankur Tomar, Farnell element14

The Internet is increasingly being complemented by the Internet of Things (IoT), which is providing a wealth of new information and enabling new forms of automation.

But IoT communications have specific requirements. Energy harvesting wireless sensor nodes are one type of device that can meet these demands.

The necessary networks that comprise the IoT are built of sensors, actuators and processors, which can be flexibly modified according to the actual demand. In the process, data storage and processing can either be done locally or within a cloud-based infrastructure. Hence, a user instructs the heating system over the Internet to raise the temperature to comfort level ahead of returning home. Here, the content or the com-mand respectively is generated by the human being, whereas the heating system processes the data and turns up the heating in a specific period of time. Additionally, wireless sensors mea-sure outdoor and room temperature which, together with the current weather forecast, can be used by the home automation system to calculate the required heating. Machines (sensors, actuators, control units) now communicate directly with users or other machines on a broad scale over the Internet.

Benefits of an internet of thingMore input (sensor) data usually yields a better insight into the system status. This additional information allows a better decision-making process considering a broader range of crite-ria. Unlike the standard approach of one or more sensors being connected to one central control unit, the Internet of Things allows the sharing and reuse of available information between different partners. Thus, the system collects data only once but uses the information for several applications.

Current control systems are usually local; for example sensors, control unit and actuators are often in close proximity and directly con-nected with each other (wired or wireless). The Internet of Things no longer requires such proximity. It al-lows centralised, or even outsourced computing resources (cloud-based computing), thus driving down infra-structure cost. The IoT also allows a dynamic creation of control networks. The networks can be formed or dissolved dynami-cally based on time, location or other parameters. For instance, cars could automatically query temperature sensors in the street to determine if there is a danger of ice on the roads and warn the driver accordingly. All the required base technologies for forming such network already exist today – sensors, actua-tors, local or cloud-based control units and IPv6 to connect all of them together.

Requirements for a connected world• Computing power is readily available both locally or cloud-

based. The main challenge is how to deploy large numbers

of sensor and actuator nodes and connect them in a suitable way.

• Installation: large numbers of new sensor and actuator nodes need to be deployed (often in an existing infrastructure).

• Scaling up in the number of deployed units due to expansion etc.

• Service and maintenance required by individual nodes have to be minimal when creating large scale networks. The vast majority of nodes in such networks needs to be maintenance-free.

• Communication between all parties involved has to be rolled out. A true Internet of Things can only be formed if all of its nodes can be accessed via Internet Protocol (IP). It is not required that the nodes themselves physically communicate via IPv6 as long as the translation between the node’s pro-tocol and IPv6 is transparent. At the same time, secure data exchange is a key consideration when sensor information and actuator commands are exchanged over the Internet.

• Finally, the cost is almost always a limiting factor, so the total cost of ownership must be low. These requirements can all be met by wireless systems giving ease of installation and scal-ability. Maintenance-free, zero cost of operation sensor and actuator nodes can only be achieved via energy harvesting wireless sensor nodes.

Energy sourcesThere are three main categories of energy that are typically used for self-powered energy harvesting devices.

Additional, less widely used, ambient energy sources include electromagnetic waves as well as chemical and bioelectric systems. The key challenge with all these energy sources is that they provide very small amounts of energy. Energy release can occur either in short bursts or as a continuous trickle. In both cases, it typically needs to be accumulated and often converted (to higher voltage levels) to be usable. This places significant challenges on the design of energy harvesting wireless sensor nodes. Specifically, such devices need to have a very energy efficient system design using a very low duty cycle (devices are sleeping most of the time) and requiring only extremely low standby currents while sleeping. The communication protocol


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used by such devices needs to be optimised for energy ef-ficiency to minimise their active time.

Energy-efficient system designSince most energy harvesters deliver only very small amounts of power, it is necessary to accumulate it over time while the system is sleeping and to lose only a small fraction of it in the process.

Therefore, the most fundamental requirement for such energy- efficient systems is that they have an extremely low idle current. This means that only a very tiny amount of energy is consumed while the system is sleeping. Standard consumer electronics devices today have a standby current in the range of a few milliamperes (mA), whereas power-optimised embedded designs typically achieve standby currents in the range of a few microamperes (uA), an improvement of factor 1,000. In com-parison, the latest generation of EnOcean energy harvesting wireless sensors require standby currents of 100 nanoamperes (nA) or less, an improvement of more than a factor of 10,000. Achieving this level of performance requires very advanced design techniques and extensive optimisation of each individual component. The second requirement is that the accumulated energy has to be used as efficiently as possible when the system is in active mode. For wireless sensor devices, the two main tasks in active state are to measure an external quantity and to wirelessly transmit information about its value. Both tasks need to be optimised for minimal power consumption. In the case of a wireless transmission, this means that the chosen

protocol must be as effective as possible. The payload associated with sensors is often small (a few bytes), therefore the protocol overhead must be limited as much as possible.

This latest requirement is difficult to achieve using IPv6 as a communication protocol even at the individual sensor level because it incurs significant overhead; the IPv6 header alone requires 40 bytes of pro-tocol data (Figure 1).

In addition to that, UDP – probably the simplest communication protocol on top of IPv6 – would require an additional 8 bytes of protocol data (Figure 2).

Based on the IPv6 and UDP header structure, the transmission of 1-byte sensor data would require an additional 48 bytes of low level protocol data. IPv6/UDP is there-fore not well suited for energy-efficient com-munication at a sensor level in a network. In comparison, the EnOcean protocol for energy harvesting wireless applications in accordance with ISO/IEC 14543-3-10 would incur only 7 bytes of protocol overhead for the transmission of 1 byte of sensor data (Figure 3). Translation between such an energy-efficient sensor protocol and IPv6 is provided by dedicated IP gateways that represent the state of each connected sen-sor node and act as their representative within the IPv6 network.

Foundation for IoTThis integrated approach of protocol trans-

lation enables all parties to communicate with energy harvesting wireless sensor and actuator networks via IPv6.

That way, a protocol such as ISO/IEC 14543-3-10, which is optimised for ultra-low power and energy harvesting wireless applications, can be used for the communication between the sensor and the gateway. This allows the deployment of a broad range of maintenance-free and cost-effective devices which are wirelessly connected.

In conjunction with IPv6 gateways, these nodes will form the foundation of the Internet of Things and enable the next tech-nology revolution. A good example of such an implementation is a Raspberry Pi coupled with EnOcean Pi. This gives users an IP gateway that will interact with any EnOcean Ecosystem whilst preserving an IP backbone. Using the Raspberry Pi a user can load open software such as OpenHab to give simple access to IP to EnOcean communications. OpenHab, like the EnOcean Alliance, is a member of the AllSeen Alliance which with its AllJoyn gives a collaborative open-source software framework that makes it easy for developers to write applications that can discover nearby devices, and communicate with each other di-rectly regardless of brands, categories, transports, and operat-ing systems.

This approach allows exchanging data with individual sen-sors even while they are sleeping and therefore unavailable for direct communication. Upon wake-up, sensors will then update their state information in the gateway and retrieve messages/commands intended for them.

Figure 1

Figure 2

Figure 3



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Energy Harvesting

Energy Harvesting From Thermoelectric Sources Gets a Boost From an Ultra-low Voltage ConverterTony Armstrong, and Dave Salerno, Power by Linear Products, Analog Devices

The proliferation of ultra-low power wireless sensor nodes for measurement and control, combined with new energy harvesting technology, has made it possible to produce

completely autonomous systems that are powered by local ambient energy instead of batteries. Powering a wireless sensor node from ambient or “free” energy is attractive because it can supplement or eliminate the need for batteries or wires. This is a clear benefit when battery replacement or servicing is inconve-nient, costly or dangerous.

Many wireless sensor systems consume very low average

power, making them prime candidates to be powered by energy harvesting techniques. Many sensor nodes are used to moni-tor physical quantities that change slowly. Measurements can therefore be taken and transmitted infrequently, resulting in a low duty cycle of operation and a correspondingly low average power requirement.

For example, if a sensor system requires 3.3V at 30mA (100mW) while awake, but is only active for 10ms out of every second, then the average power required is only 1mW, assum-ing the sensor system current is reduced to microamps during the inactive time between transmit bursts. If the same wireless sensor only samples and transmits once a minute instead of once a second, the average power plummets under 20µW. This difference is significant, because most forms of energy harvest-ing offer very little steady-state power; usually no more than a few milliwatts, and in some cases only microwatts. The less average power required by an application, the more likely it can be powered by harvested energy.

Energy harvesting sourcesThe most common sources of energy available for harvesting are vibration (or motion), light and heat. The transducers for all of these energy sources have three characteristics in common:

1) Their electrical output is unregulated and doesn’t lend itself

to being used directly for powering electronic circuits

2) They may not provide a continuous, uninterrupted source of power

3) They generally produce very little average output power, usu-ally in the range of 10µW to 10mW.

These characteristics demand judicious power management if the source is going to be useful in powering wireless sensors or other electronics.

Power managementA typical wireless sensor system powered by harvested energy can be broken down into five fundamental blocks, as illustrated in Figure 1. With the exception of the power management block, all of these blocks have been commonly available for some time. For example, microprocessors that run on microwatts of power, and small, cost effective RF transmitters and transceiv-ers that also consume very little power are widely available. Low power analogue and digital sensors are also ubiquitous.

An ideal power management solution for energy harvesting should be small, easy to apply and perform well while operating from the exceptionally high or low voltages produced by com-mon energy harvesting sources, ideally providing a good load match to the source impedance for optimal power transfer. The power manager itself must require very little current to manage the accumulated energy and produce regulated output voltages with a minimal number of discrete components.

Some applications, such as wireless HVAC sensors or geothermal powered sensors present another unique challenge to an energy harvesting power converter. These applications require that the energy harvesting power manager be able to operate not only from a very low input voltage, but one of either polarity as the polarity of the ∆T across the thermo-electric generator (TEG) changes. This is a particularly challenging prob-lem, and at voltages in the tens or hundreds of millivolts, diode bridge rectifiers are not an option.

One solution is the LTC3109, which is available in either a 4mm × 4mm × 0.75mm 20-pin QFN or 20-pin SSOP package. The LTC3109 solves the energy harvesting problem for ultra-low input voltage sources of either polarity. It provides a compact, simple, highly integrated monolithic power management solu-tion for operation from input voltages as low as ±30mV. This

capability enables it to power wireless sensors from a thermoelectric generator (TEG), harvesting energy from temperature differentials (∆T) as small as 2°C. Using two small (6mm × 6mm), off-the-shelf step-up transformers and a handful of low cost capacitors, it provides the regulated output voltages necessary for powering today’s wireless sensor electronics.

The LTC3109 uses these step-up trans-formers and internal MOSFETs to form a resonant oscillator capable of operating

Figure 1. Typical Wireless Sensor System Configuration



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from very low input voltages. With a transformer ratio of 1:100, the converter can start up with inputs as low as 30mV, regard-less of polarity. The transformer secondary winding feeds a charge pump and rectifier circuit, which is used to power the IC (via the VAUX pin) and charge the output capacitors. The 2.2V LDO output is designed to be in regulation first, to power a low power microprocessor as soon as possible. After that, the main output capacitor is charged to the voltage programmed by the VS1 and VS2 pins (2.35V, 3.3V, 4.1V or 5.0V) for powering sen-sors, analogue circuitry, RF transceivers or even charging a su-percapacitor or battery. The VOUT reservoir capacitor supplies the burst energy required during the low duty cycle load pulse when the wireless sensor is active and transmitting. A switched output (VOUT2), easily controlled by the host, is also provided for powering circuits that don’t have a shutdown or low power sleep mode. A power good output is included to alert the host that the main output voltage is close to its regulated value. Fig-ure 2 shows the circuit schematic for the LTC3109.

Thermoelectric GeneratorsTEGs are simply thermoelectric modules that convert a tem-perature differential across the device, and resulting heat flow

through it, into a voltage via the Seebeck effect. The reverse of this phe-nomenon, known as the Peltier effect, produces a temperature differential by applying a voltage and is familiarly used in thermo-electric coolers (TECs).The polarity of the output voltage is dependent on the polarity of the tem-perature differential across the TEG. Reverse the hot and cold sides of the TEG and the output voltage changes polarity.

TEGs are made up of pairs or couples of N-doped and P-doped semiconductor pellets connected electrically in series and sandwiched between two thermally conductive ceramic plates. The most com-monly used semiconduc-tor material is bismuth-telluride (Bi2Te3). Figure 3 illustrates the mechanical construction of a TEG.

A number of variables control how much voltage a TEG will produce for a given ∆T (proportional to the Seebeck coefficient). Their output voltage is in the range of 10 mV/K to 50mV/K of differential temperature (depend-

ing on the number of couples), with a source resistance in the range of 0.5Ω to 10Ω. In general, the more couples a TEG has in series, the higher its output voltage is for a given ∆T. How-ever, increasing the number of couples also increases the series resistance of the TEG, resulting in a larger voltage drop when loaded. Manufacturers can compensate for this by adjusting the size and design of the individual pellets to preserve a low resis-tance while still providing a higher output voltage. The thermal resistance of the TEG is yet another factor to take into consider-ation when choosing and matching it to a heatsink.

ConclusionWith its ability to operate at input voltages as low as ±30mV, the LTC3109 provides a simple, effective power management solu-tion that enables thermal energy harvesting for powering wire-less sensors and other low power applications from common thermoelectric devices. The product offers low voltage capabili-ties and a high level of integration to minimise the solution foot-print. The LTC3109 interfaces with existing low power building blocks to support autonomous wireless sensors and extend the battery life in critical battery backup applications.

Figure 2. LTC3109 Schematic for Unipolar Input Operation

Figure 3. Typical Mechanical Construction of a TEG



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Medical Electronics

Accessible Heart Monitoring Solutions Point to Preventative Maintainance for PeopleMark Patrick, Mouser Electronics Europe

There is strong trend data to show that the wearable elec-tronics market is increasingly influenced by what is now referred to as the Internet of Medical Things (IoMT). The

benefits of wearable devices that can measure activity and gen-eral well-being are already apparent. Devices that can relay that information to a medical professional, allowing them to monitor the health of patients recovering from a procedure or managing a long-term condition, are starting to appear. It is likely the use of these devices will further increase, not only in the medi-cal profession but amongst consumers generally interested in measuring and monitoring their state of health. Think of it as preventative maintenance for people.

One of the most informative parameters available to health-care professionals is heart activity; detecting and recording the heart’s condition can enable the diagnosis of congenital illnesses and an early warning for potentially life threatening conditions.

Accuracy is going to be crucial in this application area. Fit-

ness monitors have progressed significantly since early pedom-eters, thanks almost entirely to the development of multi-axes MEMS sensors. Similarly, examples of simple heart rate moni-tors that communicate with a smart phone app, normally over a Bluetooth connection, are also now commonplace. But to really deliver a level of accuracy that could be useful in the diagnosis of potential medical conditions, it is necessary to bring the kind of technology currently used in hospitals into our homes.

Heart shaped measurements There is a difference between pulse rate measurement, now accessible at extremely low cost through consumer devices

such as fitness trackers, and the kind of heart rate monitoring normally achieved through an electrocardiograph, or ECG. The former can provide a good indication of general heart activity during rest and active periods, but wouldn’t be accurate enough to detect the early warning signs of an impending cardiac event, or the patterns present after such an event. An ECG machine, on the other hand, can be used to more closely analyse the heart’s condition, by measuring the shape of the heart’s beats as opposed to just its rate.

ECGs are enabled through sensors attached to the skin that detect the small variations in electrical activity, present on the skin, when the heart’s cells exhibit a change in their electrical charge; so-called depolarisation and repolarisation. Detecting these changes is only part of the challenge, the signals detected

Figure 1: Microchip Technology’s vision for an ECG monitoring solution based on its technology (Source: Microchip Technology)



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then need to be filtered and analysed. Thanks to the continued development of integrated solutions this is something that can now be achieved using fewer components. This could lead to ECG machines becoming smaller, more portable, more easily operated and, of course, lower cost, representing a significant inflexion point in healthcare.

Examples of how this can be achieved in practice are beginning to appear from semiconductor vendors, such as Microchip Technology. Figure 1 shows how an ECG could be realised using a small number of devices, supported by embed-ded software. The Analogue Front End (AFE) would typically comprise an Instrumentation Amplifier such as the MCP6N11, coupled to an Analogue to Digital Converter (ADC), for example the MCP3551. The digital interpretation of the signal detected by the electrodes would then be passed through an algorithm performing FIR or IIR digital filtering. A microcontroller such as the PIC18 8-bit family is capable of performing this stage and Microchip has produced an application note detailing how to implement FIR/IIR filters using the PIC18 family (Application Note AN852).

Non-contact detectionWhile it seems likely that the use of ECG equipment will extend beyond the hospital ward, it still requires sensors to be posi-tioned on or very close to the skin, which in some cases could inhibit its use. Fortunately, new techniques for measuring the heart’s activity are constantly being developed and improved upon. This includes Ballistocardiology (BCG), which measures the heart’s activity indirectly through the use of non-contact sensors. This means it can be effective for a greater number of patients, as it can be used completely unobtrusively.

The technique works by detecting the effect of blood flow-

ing at speed in the aorta, the body’s main artery that begins at the left ventricle of the heart and travels up towards the head before changing direction to pass down through the body to the abdomen, at which point it diverges into smaller arteries. As the name may imply, BCG works by measuring the ballistic effect of blood being pumped out of the heart; that is, the ‘shock’ the body feels as the blood is pushed out of the heart and into the aorta. The great advantage of BCG is that it can be detected using non-contact sensors, and there is even research to show cameras can be used to record BCG data.

As mentioned above, the ballistic effect measured is the body’s own reaction to the acceleration of blood in the aorta as it is expelled by the heart, meaning the body exhibits a motion

opposite to that of the blood flow. If the body is immobile and positioned on a suitable platform, such as a sprung mattress, this tiny motion can be detected. The level of movement in-volved is clearly very small, and so only the most accurate sen-sors are able to detect it and extract it from the many sources of noise present. Figure 2 illustrates how the technology would be used in practice.

Modern advancements in MEMS technology have led to sen-sors sensitive enough to detect this level of movement. Murata has developed a platform based on its own MEMS sensors that can be used for BCG measurements, for patients lying in a bed. The technology is now available in two forms; a complete, packaged platform that includes a Wi-Fi module for wireless connectivity (SCA11H), and the sensor module that enables it, the SCA10H (Figure 3).

As can be seen in Figure 4, the MEMS sensor at the heart of the module is the SCA61T 3D accelerometer. The signal de-tected is very low, around 1cm/s2, or 1mg, and the environment is likely to be extremely noisy in comparison to the signal, both in terms of electrical and mechanical noise. Murata’s ultra-low noise MEMS solution, which has a noise density below 150μm/s2/√Hz, is around 20 times better than the MEMS sensors gen-erally used in consumer wearables.

The BCG sensor detects the movement in the sprung mat-tress caused by the heart pumping, and uses this information to extrapolate physiological data such as the heart rate and its variability, as well as more critical parameters including relative stroke volume. From that, respiration rate can be extrapolated, which means the technology can also be used to monitor the quality of sleep a patient experiences, and even detect when the bed is occupied.

In tests conducted by Murata to compare the BCG sensor with an ECG sensor to measure heart rate variability, it was found that there was a better than 96% correlation between the results achieved by the BCG and ECG solutions. This is clear evidence that the convenience of a BCG sensor, with respect to an ECG, could deliver real benefits in patient care and even be used as a matter of routine health monitoring in the home.

ConclusionAdvancements in sensor technology and embedded process-ing are leading to breakthroughs in health care. As the concept of home healthcare enabled by the IoMT gains acceptance we can expect more consumers to adopt technology that not only allows existing conditions to be monitored but will enable us to take more interest in our health and control of our general wellbeing.

Figure 2: How BCG technology can be used in practice (Source: Murata)

Figure 3: The SCA10H BCG Module from Murata features one its most accurate MEMS sensors (Source: Murata)

Figure 4: A block diagram of the SCA10H BCG Module (Source: Murata)


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Medical Electronics

Listening to the Market: The Emergence of Over-The-Counter (OTC) Hearing AidsBy Steven Dean, ON Semiconductor

Over-The-Counter (OTC) reading glasses allowed con-sumers who were beginning to struggle with mild, mid-life sight issues to quickly and easily obtain solutions

without visiting an optician. We are now in the early stages of defining a new classification of device for those who are experi-encing mild and moderate hearing loss. Although easier access to hearing aids will be welcomed by many, one large piece of the puzzle - how these devices will ‘fit’ each patient - has yet to be defined.

Following a US Federal Trade Commission (FTC) workshop entitled “Now Hear This” in April 2017, President Donald J. Trump signed the Food and Drug Administration (FDA) Reau-thorization Act 2017 into law. A similar process is taking place in Europe and, while the debate continues, there is recognition by the World Health Organization that the aging population in Eu-rope is creating a generation of people suffering from untreated hearing loss. Concerns exist over the regulation of Personal Sound Amplification Products (PSAPs), but the results of a recently concluded six-year study by Professor Bridget Shield suggest the economic impact of not treating hearing loss could reach €500 billion across the EU each year, due to lost produc-tivity and impaired quality of life.

Included within the US Act is the OTC Hearing Aid Act that will provide greater public access to affordable OTC hearing aids. As a result, the FDA is required to create and regulate a category of OTC hearing aids to ensure that they meet the same high standards for safety, consumer labeling and manufacturing protection that all other medical devices must meet. The result-ing products will be welcomed by consumers looking for an easier, more convenient and affordable solution to treating their mild or moderate hearing loss.

Up to 48 million Americans are affected by some degree of hearing loss according to the National Center for Health Statistics, yet Medicare and many private insurance plans do not cover the cost of hearing aids. While treatment is effectively free in many European countries, many stakeholders agree that improving accessibility and affordability is a key priority. The reality is that many people simply cannot afford the cost of cur-rent devices, and often people require two hearing aids.

Price is not the only consideration. For hearing aids, the key to successful adoption remains in the patient fitting process. The FDA has yet to introduce guidelines and regulations in this regard for OTCs where in-person fitting and counselling by trained professionals will not be available. Unlike reading glass-es, hearings aids cannot simply be bought and worn. They are complex devices that require additional software adjustments to a patient’s individual needs or preference. This is essential to hearing aid adoption as devices that are not properly fit can lead to discomfort, or even further hearing damage.

Previous attempts to meet the market need for lower-cost devices have been unsuccessful due to a lack of available fitting options. While the introduction of PSAPs was a deliberate move away from the clinical space; the new generation of OTCs is a step back and one that many believe to be in the right direction and could actually expand the market for hearing aid manufac-

turers. This will mark the first time the industry will recognise a lower-cost, turnkey device within the hearing aid categorisation.

The barriers to entry into the hearing aid market have re-mained high in terms of need for expertise and resource. Hear-ing aid design is very complex, requiring a thorough knowledge of Digital Signal Processing (DSP), digital audio, and extreme low power optimisation.

Even at the lower price points of OTC hearing aids, consum-ers will still demand high quality devices that are small and dis-crete. Also at the top of the list of user demands are excellent audio quality, long battery life and, ideally, the ability to man-age the device using a smartphone. Yet this OTC movement doesn’t necessarily preclude traditional dispensaries from the channel or fitting customers as before. Traditional dispensaries can benefit from new technologies, simplified fitting tools, and device management born out of this as well.

Until recently, system-level options available to hearing aid manufacturers have been limited to either fixed-function or open-programmable hardware platforms. While fixed-function solutions do not provide the design flexibility required by mod-ern hearing aids, many companies do not have the resources to work with an open platform. In a market that is evolving as quickly as hearing aids, there is a strong need to provide an alternative design solution.

In other industries, leading semiconductor companies have increasingly recognised the opportunity to support designers



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by providing development kits and often complete software/firmware solutions alongside their products. However, up until recently, only somewhat basic and rudimentary solutions have been available for the hearing aid market.

The availability of development environments that provide a complete framework, including algorithms and firmware, Software Development Kits (SDK) and configuration tools, can provide a turnkey solution to unlock the OTC market.

As an example of this type of development kit, ON Semicon-ductor’s Ezairo Preconfigured Suite (Pre Suite) is a development toolkit based on the Ezairo 7100 DSP, which is intended to enable turnkey hearing aid solutions. Ezairo Pre Suite contains algorithm and firmware bundles, software for fine-tuning algo-rithms and features, and a cross-platform SDK which can be used to develop fitting software and wireless applications.

The new wirelessly-enabled Ezairo 7100 DSPs are the first hybrid solution to be supported by the Ezairo Pre Suite. Designed specifically for hybrid applications, these firmware bundles feature up to eight channels of Wide Dynamic Range Compression (WDRC) and a collection of hearing aid algorithms ideal for developing Bluetooth low energy technology-enabled hearing aids and OTC devices.

Bluetooth low energy technology is a new area for many manufacturers. By including built-in wireless functionality, companies of all sizes are able to provide features like smart-phone based wireless tuning and audio streaming to hearing aid wearers.

Firmware development is always a challenging aspect in any project. The preconfigured algorithms in the Ezairo Pre Suite eliminate the need to invest in DSP algorithm developers and coders, further allowing all hearing aid companies better time to market.

For OTC hearing aids, perhaps the most crucial piece of the Ezairo Pre Suite is the provided cross-platform SDK. Support-ing both iOS and Android operating systems, the SDK offers a platform for manufacturers to easily create both fitting software and wireless mobile applications.

While the opportunity for OTC hearing aids became very real with the passing of the FDA Reauthorization Act, technical challenges could limit consumer choice in the initial phases as companies struggle to bring products to market.

By sourcing turnkey solutions with all necessary IP included, and by leveraging the supplied firmware, especially the Blue-tooth low energy technology know-how and preconfigured DSP algorithms, customers can quickly bring their products to market.

In this scenario, there are many winners but those who ben-efit the most will be the consumers who will be able to enjoy a wider selection of devices with improved functionality, perfor-mance, and user control at competitive price points.



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IoT Displays

As Data Rates and Power Consumption are Restricted, How Can IoT Displays be Implemented?HD Lee, CTO, Pervasive Displays

In the same way as personal computers, the Internet and smart devices have fundamentally changed the way we live, communicate and do business, and the Internet of Things

(IoT) is rapidly connecting our physical world to the cloud, al-lowing us to monitor and control far more than ever before.

Machines now communicate directly with other machines, but when human interaction is desirable or necessary, some form of display is useful. With the low levels of data and minus-cule power demands associated with the IoT, providing displays is proving a challenge for designers.

This article will look at the growth of the IoT and some of the technologies behind it, including reliable narrowband com-munications, before showing how displays that strike the right balance between functionality and power can be implemented.

The IoTWithout question, the IoT is huge, and is growing rapidly – both in terms of connected devices and infrastructure. Cisco once estimated that 2004/2005 was the point at which we surpassed one device connected to the IoT for every living person on the planet. Although some of the early IoT forecasts predicting tens of billions of devices have been reduced a little, the forecasts remain significant.

Gartner estimates 8.3 billion devices at the end of 2017, in-creasing to 11.2 billion by the end of 2018 and almost doubling to 20.4 billion by 2020. Within these figures approximately two-thirds are for consumer applications. While spending is forecast to increase from US$2.1 billion in 2018 to US$2.9 billion in 2020, it is not growing as fast as the unit count, strongly imply-ing that prices will fall – partly through price erosion, but also as more small, simple, devices become connected.

Opportunities and challengesWhile the IoT will fundamentally change our lives as consumers, the impact on business will be equally dramatic. By connecting more than ever before, including smart factories and remote environmental data, businesses will be able to reduce operating costs and increase productivity as well as generating complete-ly new revenue streams and business models.

Yet, achieving these deliverables is not without some signifi-cant hurdles to overcome. The widespread roll-out of the IoT is one of its greatest advantages and also one of its greatest challenges. Each remote node needs power and the ability to transmit data back to a central location, via the cloud. Frost & Sullivan developed a useful model that demonstrates the four key considerations for developing IoT solutions. The ‘4C’ model covers Capacity (data rate or data throughput), Consumption (battery life – often measured in years), Coverage (the ability of networks to provide effective coverage to maintain connectivity) and Cost (both for the node and for network costs).

Currently, around 90% of IoT connectivity is provided by

some form of local area network (LAN) such as Ethernet/WiFi, and more local connectivity (Bluetooth, Zigbee, RFID and oth-ers) is used within buildings and other short-range applications. Cellular technology is currently used for wider area coverage, although it is relatively expensive in terms of cost and power consumption. It also suffers from patchy coverage, which can cause intermittent connectivity.

In order to address the shortcomings of cellular a range of new technologies under the generic heading low power wide area network’ (LPWAN) are emerging. LPWAN covers both non-cellular and cellular technologies, but the cellular approach delivers the greatest coverage/range.

The two cellular approaches are Narrowband IoT (NB-IoT) and LTE-M Cat-M1, which are very similar in many respects. Both approaches are based on orthogonal frequency division multiple access (OFDMA) technology and operate in the 450 MHz to 3.5 GHz range. NB-IoT has a slightly longer range, at more than 15 km outdoors, but trades this for a maximum data throughput of 250 kbps, compared with 1000 kbps for LTE-M.

Cost is where the two cellular LPWAN technologies really differ, with the hardware and monthly connectivity costs for NB-IoT being approximately 25% of those associated with LTE-M.

Displays and the IoTWhile much of the IoT is based on machine-to-machine (M2M) communications, often humans need to interact and some form of display is required to allow data to be rapidly reviewed and assimilated. In a central monitoring station, power is normally readily available and sophisticated dashboards can be created. However, having some form of display at the remote node can significantly enhance the functionality and usefulness, display-ing key parameters or basic instructions to a human operator.

Providing this functionality presents challenges, especially with the increased use of LPWAN technologies where data throughput is reduced. Sophisticated touchscreen display tech-nologies such as LCD demand significant amounts of data and also require significant power, whereas the use of LED-based indicators (as is common in embedded systems) can meet the data and power needs, but provides scant information that rarely meets the needs of the user.

E-paper: Many of us are already familiar with e-paper technology without necessarily realising it, as it forms the backbone of popular reading devices such as the Amazon Kindle. E-paper is a low-power display technology that resembles the appearance of traditional paper and ink. Each display contains many thou-sands of tiny capsules/pixels, which contain black and white ink particles that are negatively and positively charged. By applying appropriate charges across each ink-filled capsule the colour can be changed, thereby creating high-resolution images.

Figure 1: Frost & Sullivan 4C model for IoT considerations

Figure 2: E-paper displays contain thousands of capsules filled with charged ink particles



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E-paper has some fundamental attributes that make it ideal for low-power, low-data-rate IoT applications. Firstly, the technology is bistable, meaning that once an image has been created on the display, no further power is required to maintain the image. Secondly, in common with ink and paper, it is reflec-tive, using reflected light to make the image visible, rather than relying on a backlight as LCD displays do. Not only does this significantly reduce the power consumption, it also makes the displays much thinner and lighter than LCDs.

Given the remote location of many IoT nodes, power consumption is critical to success. Many of these devices are powered by small batteries such as coin cells, and the cost and inconvenience of regularly travelling to remote locations to replace a battery can be significant.

Many IoT applications deal with relatively slow-moving parameters, and the displays only need to be updated when a human operator is present, meaning that the number of required updates is relatively low. In fact, e-paper technology is an ap-propriate choice for many modern IoT applications including smart metering, smart cities, smart buildings, consumer and ag-ricultural/environmental usage – which is almost always remote.

If we consider a practical example where a 2-inch display needs to continuously display data, with six updates per day, we can illustrate the significant difference between an e-paper

module and a similarly sized TFT LCD display. Typical power consumption for the e-paper module is 2.33 mA whereas the TFT LCD display would consume 30 mA. The power consump-tion for the e-paper display is 0.01 mAh daily, or 3.29 mAh an-nually. In comparison, the TFT LCD requires 720 mAh per day, or 262,800 mAh each year.

With a basic CR2032 coin cell that has a typical capacity of 225 mAh, the TFT LCD display would be completely non-viable, requiring several battery changes per day. However, the e-paper display would not have used 10% of its capacity after five years and would only need to be replaced once in the average human lifetime.

SummaryThe IoT is already significant and will only continue to grow over the next few years, becoming more widespread than almost any other technology. In order to sustain this growth trajectory, technology needs to evolve and become more suitable for IoT applications. One example of this is the communications tech-nology that is moving to LPWAN, thereby delivering sufficient capacity and coverage for the IoT, while reducing consumption and cost.

As the communications backbone is right-sized, so technol-ogy advances are required in other areas. Once such area is displays, where common LCD TFTs are patently unsuitable for modern IoT applications. Fortunately, the availability of extreme-ly low-power e-paper displays delivers the functionality required for remote IoT nodes, while vastly exceeding the demanding power goals.

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Figure 3: E-paper is appropriate for a wide range of IoT applications



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