In Search of the Energy-Efficient Family Car

Written by: Karen Lightman, Executive Director, MEMS Industry Group
(as published in Design News on 09/06/2013)

Buying a car just isn’t as easy as it used to be, especially when you know just enough about alternative-fuel-source vehicles to make that decision very difficult. As my husband and I debate the merits and faults of energy-efficient cars (as the end date of his leased Prius looms in the background), I feel as though we must make a smart choice that is right for us and right for the planet. Perhaps you relate to such a quest for the perfect car that balances safety, comfort, fuel efficiency, and style.

When I entered this decision tree of what fuel-efficient car to buy, I initially thought that an electric vehicle (EV) would be the simple solution. EVs, which run on chargeable batteries, seem to make sense for our family. We live in an urban area and rarely take long trips requiring a long charge. We’ll just plug the car in at night and stop using petroleum that pollutes the air. Right?

Not quite. As I started discussing the decision with my MEMS colleagues (all with their EEs and MEs), I quickly learned that it’s not that simple. First, the biggest limitation is the battery itself. The energy-to-weight ratio for EVs is quite abysmal compared with gasoline. Up to one-third of an EV’s total weight can be attributed to the battery pack alone, and most of the batteries hold a charge for a few hundred miles at best. That’s a deal breaker for many.

Tesla appears to be the only EV company that is seriously attacking the battery issue. Its CTO has said battery energy density is improving about 7 percent a year. This clearly shows that his company understands one of the biggest roadblocks to EV adoption. Tesla has designed a beauty of a lightweight car that is chock full of MEMS/sensors and showcases an iPad-like dash between the passenger and driver. Plus it has two trunks; that is just so cool. (It’s the reason my 12-year-old daughter insists we buy a Tesla.)

Until we have cars that run on solar panels, energy is never free. Even if you decide to buy a Tesla, you have to think about where the energy is generated to recharge the battery every night. For me in Pittsburgh (and for most of the Northeast), the source is typically coal. Uh, oh. That means I would deplete more fossil fuels and release more greenhouse gases if I bought an EV. Another important issue is the disposal of heavy-lead lithium batteries. Some EVs need to replace their batteries after three years. So if you are the average American who holds on to a car for five years, you’ll need to dispose of (and pay for) two batteries and consider the environmental impact of that decision.

Let’s face it — the batteries for EVs (and for most consumer electronics) are still inefficient. Here’s where my MEMS brain starts to activate and I start thinking about energy harvesting. Can’t we find ways through MEMS to harvest the car’s vibrations at least to power its electronics?

I bet the folks at MicroGen Systems are already looking into this. I actually know of a few more companies (big and small) that are looking into ways to make vehicles smarter and energy efficient from the get go through a combination of MEMS and sensors. Examples include energy harvesters in the tire that capture the vibrations and power the tire-pressure monitoring system, as well as sensors embedded into an engine to maximize fuel efficiency. Take it one step further, and HVAC monitoring systems managed by an in-car sensor network could keep passengers comfortable as the vehicle passes through varying daylight and temperature conditions. MEMS will make this happen.

I guess I will have to wait until there’s smarter battery technology that recharges an EV by green energy. In the meantime, I’ll be asking my local car dealer how many MEMS and sensors are inside the vehicle. The car with the most MEMS wins.

MIG Visits the AUVSI Unmanned Systemss Conference

Written by: Monica Takacs, Membership Director, MEMS Industry Group

From robotic ground vehicles that enter areas too dangerous for humans, to maritime vehicles that explore and map underwater caves, and drones used for agricultural and environmental applications, the unmanned vehicle systems appears to be a growth industry for MEMS.

MIG attended the AUVSI (Association for Unmanned Vehicle Systems International) conference in Washington, DC, August 13-14 to check out all of the MEMS devices found in these unmanned vehicle systems. Inertial MEMS sensors were featured throughout the show and many of the exhibitors demonstrated the cost, size, and power consumption advantages that MEMS has over traditional inertial measurement systems (IMU) like fiber optic gyros.

Several MIG members were at the conference showcasing their technologies.

Analog Devices featured their signal processing technologies for advanced unmanned systems for defense & civilian applications, including their MEMS based inertial sensor technology.

Epson introduced their M-V340 IMU for unmanned vehicles and other space- and weight-sensitive applications.  They claim it’s smallest IMU among high-performance IMUs having gyro bias instability of 10 dph or less (as of the beginning of August 2013, according to Epson’s research.)

Honeywell presented their HG1930 IMU for flight control, navigation of UAVs, missiles, projectiles, and munitions that include inertial MEMS sensors designed, developed, and manufactured in-house.

Meggitt showcased their thermal management solutions for unmanned platforms, and projectile tracking technology that track bullets to large missile and can provide weapon performance data from a target platform or threat notification on a tactical platform.

PNI Sensor Corporation displayed their 9-axis sensor fusion pinpoint heading and orientation technology and algorithms for the consumer, military, and scientific markets.

Sensonor showcased their tactical grade STIM300 IMU, a non-GPS aided IMU, containing 3 MEMS gyros, that is suitable for various commercial and defense guidance and navigation applications.

Xsens demonstrated their MTi 100-series, their high performance product line that features vibration-rejecting gyroscopes and a sensor fusion algorithm that overcomes limitations in Kalman Filtering.

VetorNav Technologies displayed their VN-200 GPS-Aided Inertial Navigation System (GPS/INS) which incorporates a suite of MEMS-based 3-axis accelerometers, gyroscopes, and magnetometers, along with a barometric pressure sensor and a high-sensitivity GPS module in a surface mount package.

Guest Blog – MEMS New Product Development, Critical Design and Process Steps for Successful Prototypes (Part 2)

David DiPaola, DiPaola Consulting, LLC,

The fourth article of the MEMS new product development blog is Part 2 of the critical design and process steps that lead to successful prototypes.  In the last article, the discussion focused on definition of the customer specification, product research, a solid model and engineering analysis to validate the design direction.  The continuation of this article reviews tolerance stacks, DFMEA, manufacturing assessment and process mapping.

A tolerance stack is the process of evaluating potential interferences based on the interaction of components’ tolerances.  On a basic level, a cylinder may not fit in a round hole under all circumstances if the cylinder’s outside diameter is on the high size and the inside diameter of the hole is on the lower size causing an interference when there is an overlap of their tolerances.  This situation can become complex when multiple components are involved because it results in the number of variables reaching double digits.  A simple approach to tolerance stacks is using a purely linear or worst case approach where full tolerances are added to determine potential for interference.  However, experience from producing millions of sensors shows this approach is overly conservative and a non optimal design practice.  If tolerances of the assembly follow a normal distribution, are statistically independent, are bilateral and are small relative to the dimension, a more realistic approach is a modified root sum of the squares (MRSS) tolerance stack technique.  In this approach the root sum of the squares of the tolerances are multiplied by a safety factor to determine the maximum or minimum geometry for a set of interrelated components.  The safety factor accounts for cases where RSS assumptions are not fully true.  This approach is only recommended when 4 or more tolerances are at play.  If only 2 tolerances are present as in the first example above, it is recommended to perform a linear tolerance stack.  In some cases, linear tolerances need to be added to a MRSS calculation (MRSS calculation + linear tolerances = result).  Pin position inside a clearance slot for anti-rotation is linear tolerance that is added to a MRSS calculation.  Reasoning for this is the pin can be any location in the slot at any given time and does not follow a normal statistical distribution.

An example of a MRSS tolerance stack is provided below to review this concept in more detail.    Let’s determine if the wirebond coming off of the sense element will interfere with the metal housing.  A modified RSS tolerance stack shows line to line contact and only a small adjustment in the design is needed to resolve the issue.  The linear tolerance stack shows a significant interference what requires a larger adjustment.  Dimensions and tolerances are illustrative only.

Figure 1

MEMS Sensor Package (mm)

Fig 1

Figure 2

Modified Root Sum Square Versus Linear Tolerance Stack Approaches

0.17 > SF*(((T1^2) + (T2^2) + (T3^2) + (T4^2) + (T5^2))^(0.5))        MRSS Approach

0.17 > 1.2*((0.01^2 + 0.05^2 + 0.025^2 + 0.10^2 + 0.08^2)^0.5) = 0.17

0.17 > T1 + T2 + T3 + T4 + T5        Linear Approach

0.17 > 0.01 + 0.05 + 0.025 + 0.1 + 0.08 = 0.27

An excellent text on this subject is Dimensioning and Tolerancing Handbook, by Paul J. Drake, Jr. and published by McGraw-Hill.

DFMEA, design failure mode and effects analysis. is another tool that is extremely effective to identify troublesome areas of the design that need to be addressed to prevent failures in validation and the field.  Simply put this is a systematic approach to identify potential failure modes and their effects and finding solutions to mitigate the risk of a potential failure.  A Risk Priority Number (RPN) is then established based on rating and multiplying severity, occurrence and detection of the failure mode (severity*occurrence*detection = RPN).  The input to the tool is the design feature’s function, the reverse of the design function, the effect of the desired function not being achieved, and the cause of the desired function not being achieved.  There is also an opportunity to add design controls prevention and detection.  The outputs are the corrective actions taken to mitigate risk of a potential failure. Figure 3 shows an brief example of this approach for a MEMS microphone.

Figure 3

Design Failure Mode and Effects Analysis (click to view full size)

Fig 3

Further information on DFMEA can be found at Six Sigma Academy or AIAG.  Corrective action section left out of illustration for clarity.

It is also extremely important that the manufacturing process be considered from the first day of the design process.  Complete overlap of design and process development are the true embodiment of concurrent design.  The following illustration depicts this well:

Figure 4

Concurrent Design

Fig 4

Hence before a MEMS design is started, discussions should be initiated with the foundry, component fabrication suppliers and the process engineers responsible for the package assembly.  These meetings are excellent times to review new capabilities, initial ideas and explore new concepts.   Considering the design from a process perspective simultaneously with other design requirements leads to highly manufacturable products that are often lowest cost.    In essence, the design engineer is performing a constant manufacturing assessment with each step in the design phase.  This methodology also encourages process short loops in the design phase to develop new manufacturing steps.  This expedites the prototype process with upfront learning and provides feedback to the design team for necessary changes.  The additional benefit of this approach is the boarder team is on board when prototyping begins as they had a say in shaping the design.

Another tool to thoroughly understand the process in the design phase is process mapping.  Using this methodology, process inputs, outputs, flow, steps, variables, boundaries, relationships and decision points are identified and documented.  The level of detail is adjustable and to start there can be a broad overview with more detailed added as the design progresses.  This quickly provides a pictorial view of the process complexity, the variables effecting the design function, gaps, unintended relationships and non value added steps.  It can also be used as a starting point for setting up the sample line in a logical order to assemble prototypes, estimating cycle time and establishing rework loops.  To further clarify this method, a partial process map for a deep reactive ion etch process is provided:

Figure 5

Partial Process Map of Deep Reactive Ion Etch Process

Fig 5

This process map is not all inclusive but illustrative of the process flow, critical parameters, inputs and a decision point.  The personal protection equipment, tools used and relationships in the process are omitted for brevity.  With this level of process detail available to the design team, the complexity of feature fabrication can be evaluated, anticipated variation from process parameters can be analyzed and much more possibly prompting design changes.
Knowledge of and attention to detail in these eight critical, yet often overlooked steps are essential in the design of highly manufacturable, low cost and robust products.  These methodologies create a strong foundation upon which additional skills are built to provide a balanced design approach.  In next month’s blog, the design review process and a checklist will be discussed to help engineers prepare for this important peer review process.

Updated Bio:


David DiPaola is Managing Director for DiPaola Consulting a company focused on engineering and management solutions for electromechanical systems, sensors and MEMS products.  A 17 year veteran of the field, he has brought many products from concept to production in high volume with outstanding quality.  His work in design and process development spans multiple industries including automotive, medical, industrial and consumer electronics.  He employs a problem solving based approach working side by side with customers from startups to multi-billion dollar companies.  David also serves as Senior Technical Staff to The Richard Desich SMART Commercialization Center for Microsystems, is an authorized external researcher at The Center for Nanoscale Science and Technology at NIST and is a Senior Member of IEEE. Previously he has held engineering management and technical staff positions at Texas Instruments and Sensata Technologies, authored numerous technical papers, is a respected lecturer and holds 5 patents.  To learn more, please visit

Thinking Outside the Mobile ‘Box’

Written by: Karen Lightman, Executive Director, MEMS Industry Group
(as published in Design News, August 1, 2013)

By now you’ve probably figured out that there are a bunch of micro-electromechanical systems (MEMS) devices inside smartphones and myriad other mobile consumer devices. But did you know that MEMS is also revolutionizing how dairy cows are managed and that it’s a potentially $40 billion business?

I learned this recently from Dr. Alissa Fitzgerald’s presentation at Sensors Expo 2013, “Thinking outside the (mobile) box: Other important high-value applications for sensor fusion.”

The cows wear MooMonitor, a collar outfitted with a motion sensor (MEMS accelerometer) and a temperature sensor that indicates when the mama cow is hitting peak fertility and is ready for reproduction. It’s called a “bovine estrus cycle detection” app, and you can get updates from the cows via iPhone right there on the dairy farm. There are a staggering 265 million dairy cows in the world that could wear these collars, and whose farmers can benefit from this application. This is a fine example of someone figuring out a way to make a ton of money in MEMS with a non-consumer mobile device.


The MooMonitor collar.
(Source: Dairymaster)

Fitzgerald identified several other MEMS-based applications in markets that some might call “unsexy” but that actually have big potential. In home maintenance equipment, we have robotic vacuum cleaners (Roomba), gutter cleaners (Looj), and even pool cleaners (Mirra) — all made by iRobot. Even the big home appliance makers like Whirlpool and LG are getting into the action with “smart-home” goods such as clothes dryers embedded with humidity sensors.

While the thermostats that control HVAC might not seem like a huge market opportunity, Fitzgerald encouraged us to think again about this humble piece of electronics. There are 10 million thermostats purchased in the US each year, and 250 million already installed in homes and light commercial buildings. That’s a market ripe for smart MEMS-enabled systems that can intelligently sense a home’s/office’s heating/cooling needs.

Enter the Nest Learning Thermostat that has multiple MEMS temperature sensors, IR motion detectors, and behavior analysis and prediction, and voila! You finally have a thermostat that can save you money on your HVAC. And the best news yet? Nest is intuitive, so you don’t have to read a huge manual on how to program it. Fitzgerald estimated that based on the annual sale unit numbers, and estimating the cost of a thermostat at $50 to $250, the total available market for thermostats to control household HVAC would be at least $0.5 billion and possibly as high as $2.5 billion annually in the US. It’s looking a lot sexier now, right?

The success of MEMS beyond the mobile-consumer space is still a well-kept secret. While health/fitness and medical devices are gaining some ground, Fitzgerald reminded us that there are many other huge industries that are often overlooked by MEMS product companies and market analysts. These include oil and gas, steel, agriculture, textiles, and mining, for starters. Fitzgerald believes that billion-dollar business opportunities are out there for companies that can think outside the box, instead of just providing more cool stuff for urban gadget hounds.

So let’s hear it for MEMS-enabled products that help people in other large industries to get their work done in the oil fields of Texas and on the dairy farms of Wisconsin.

Guest Blog – MEMS New Product Development, Critical Design and Process Steps for Successful Prototypes (Part 1)

David DiPaola, DiPaola Consulting, LLC,

In the third article of the MEMS new product development blog, critical design and process steps that lead to successful prototypes will be discussed.  These items include definition of the customer specification, product research, a solid model, engineering analysis to validate design direction, tolerance stacks, DFMEA, manufacturing assessment and process map.  With the modeling and analysis tools available and short loops for both design validation and process development, it is possible and should be expected to have functional prototypes on the first iteration.

Thorough review of the customer specification and an understanding of the application are two of the most critical steps in developing a prototype.  Without this knowledge, its a guess on whether the design will be successful meeting the performance objectives with next to zero quality problems.  The issues often encountered are the customer specification is poorly defined, it does not exist or there are gaps between customer targets and supplier performance.  It is the responsibility of the lead engineer to work with the customer to resolve these issues in the beginning stages of the prototype design to ensure a functional prototype is achieved and is representative of a product that can be optimized for production.   Furthermore, this specification creates an agreement between the supplier and customer on expectations and scope.  Should either of these change during the project, the deliverables, cost and schedule can be revisited.  Expectations and scope include package envelope, application description, initial and performance over life specifications, environmental, mechanical and electrical validation parameters, schedule and quantities for prototype and production.  In this process the supplier and customer review each item of the specification and mark it as acceptable as written or needs modification to be met given current knowledge.  There can also be area of further research and development before an agreement on the topic can be reached.  This entire process is documented and signed by both parties as a formal contract.  Then as more is learned about both the product design and application, modifications to the agreement can (and likely will) occur with consent of both parties.

Product research is another area of significant importance to the prototype process. This research has several branches including technology to be used, existing intellectual property, materials, design approaches, analysis techniques, manufacturing processes to support proposed design direction and standard components available to name a few.  Product research will also involve reaching out to experts in different fields that will play a role in the product design.  This is the initial data collection phase of learning from previous works through reading patents, journal articles, conference proceedings and text books and building a team of qualified professionals.  This process is sometimes chaotic and over whelming while wading through mounds of information in search of a viable design path.  However, this only lasts for a short period as trends start to form, innovation is birthed and a path is forged.

Parametric, 3D modeling is no longer a luxury but a must have in the design and prototype process.  It is essential for visualizing the design, documenting it and analyzing function, geometric properties and potential interferences.  However, use of the solid model should not stop there.  The documented geometry can be imported through a live link or other means to various other tools such as CNC machining, finite element analysis, tolerance stack analysis, motion visualization, fabric pattern generation prior to stitching, mold flow analysis, electrical simulations, equipment interactions, process development and much more.  The solid model should be considered a starting point for a much larger analytical model that is used to describe the fabrication, function and performance of the product and its components.  Once the solid model is complete, it is also extremely helpful to make stereolithography (SLA) or 3D printed components that can be felt, observed and often times used for preliminary product testing.  For a trivial cost, SLA’s can provide a wealth of information prior to prototype and help sell the design to colleagues and customers.

As highlighted in the previous paragraph, engineering analysis is the process used to validate the design and process direction theoretically.  The analysis can take the form of a manual hand calculation of deflection to the sophistication of finite element analysis predicting the strain in the diaphragm of a MEMS pressure sensor due to deformation of the surrounding package under thermal conditions.  The key to successful analysis is not only proper engineering judgment on parameters and attention to detail in model creation but validation of the analysis through experimentation or other theoretical means.  For example, the FEA results of a MEMS diaphragm under large deflection can be compared to other theoretical calculations of a round plate under large deflection that has been validated with experiment.  Correlation of the results suggest your model is in the ballpark and can be used to evaluate other parameters such as stress and strain.  In this analysis phase, the global model is often comprised of several smaller models using different analytical means that are then tied back together for a prediction of performance.  With many live links between several pieces of analytical software and the power of today’s computers, this process is becoming more efficient with better overall accuracy.

To better illustrate the points above, a case study of a MEMS SOI piezoresistive pressure sensor will be reviewed.  This pressure sensor was designed for operating pressures of 1000 – 7000 KPa. Due to the pressure range used, the surface area of the sensor that was bonded to the mating package substrate needed to be maximized while minimizing the overall foot print to increase the number of sensors per wafer.  Hence a deep reactive ion etch was used to obtain near vertical sidewalls.  A thicker silicon handle wafer was used to provide additional strain isolation from the sensor package while staying within a standard silicon size range for lower cost.  The silicon reference cap provided a stable pressure reference on one side of the sensor diaphragm.  Its geometry was optimized for handling, processing and dicing.

A solid model was created of the design including the wirebond pads, aluminum traces, interconnects, oxide layers and piezoresistors on the silicon membrane wafer.  In addition, the cap and handle wafers were modeled.  Although not shown here for proprietary reasons, each layer of the membrane was modeled as though it was fabricated in the foundry.  This enabled the development of a process map and flow.  Finite element analysis of the diaphragm under proof pressure loads showed that the yield strength of the aluminum traces could be exceeded when in close proximity to the strain gages.  This can cause errors in sensor output.  Hence doped transition regions were added to keep the aluminum out of this high stress region.  A comprehensive model of the piezoresistive Wheatstone bridge was created to select resistor geometry and predict the performance of the sensor under varying pressure and thermal conditions.  Strain induced in the gages from applied operating pressure and resulting deflection of the diaphragm was modeled using finite element analysis.  A model was also created to determine approximate energy levels needed to dope both the piezoresistors and transition regions.  This information was critical in discussions with the foundry in order to design a product that was optimized for manufacture as doping levels and geometry were correlated.   Furthermore short process loops were developed at the NIST Nanofab to optimize etch geometry and validate burst strength.

It is important to note that the design of the sense element was designed with constant feedback from the foundry and their preferences for manufacturing.  In addition, the sense element and packaging were designed concurrently as there was significant interactions that need to be addressed.  Design of the sense element and packaging in series would have resulted in a non optimized design with higher cost.  In the end, a full MEMS sensor specification was developed and provided to the foundry for a production quote and schedule.  Through working directly with the foundry, optimizing die size and designing a sensor for optimum manufacture, over 60% improvement in cost was achieved over going to a full service MEMS design and fabrication facility.

fig 1

Due to the length of these topics, stay tuned for next months blog for Part 2 of this article.  In that segment other critical steps including tolerance stacks, DFMEA, manufacturing assessment and process maps will be reviewed.



David DiPaolaDavid DiPaola is Managing Director for DiPaola Consulting a company focused on engineering and management solutions for electromechanical systems, sensors and MEMS products.  A 16 year veteran of the field, he has brought many products from concept to production in high volume with outstanding quality.  His work in design and process development spans multiple industries including automotive, medical, industrial and consumer electronics.  Previously he has held engineering management and technical staff positions at Texas Instruments and Sensata Technologies, authored numerous technical papers and holds 5 patents.  To learn more, please visit

Guest Blog: Tale of a Very Long Tail

Submitted by: Bryon Moyer, Editor of EE Journal.

I cut my engineering teeth on programmable logic and circuit design (bipolar, ECL). Nothing happens in those fields without tools, and so we have a massive EDA industry. OK, not as massive as they might like, given their constant kvetching about how the market never seems to grow, but it’s sizable and well established.

So I’m used to an environment dominated by a few big companies. The little companies around them mostly act like quantum fluctuations to feed the big guys. You start a company, and if you’re successful, you’re sucked into a big guy. If not, you blink out of existence like so much energy dissipating back into the ether. Those few companies that never manage to disappear, but keep trundling along, run the risk of being treated as walking wounded.

Having spent a couple years now trying to parse the MEMS industry for EE Journal, I’ve found a very different dynamic. And any stroll through the Sensors Expo (this year’s edition just finished up) will reinforce that fact. Just when you thought you knew the players, you find out how many more there are that you had no idea existed.

It feels to me like this is a result of the long years of slogging that has characterized the MEMS industry. Until recently, there has been no hockey stick. A very few relatively recent high-volume applications like airbag accelerometers have given hope to the stalwart that their efforts can achieve commercial success, but it’s been hit and miss, and not all boats have been lifted by the rising tide of visibility for the industry.

My sense of the structure is that there are three categories of MEMS merchant. There are a couple big guys – you know who they are – and their message tends to be, more or less, “We do it all; you don’t need anyone else.”

Next are some companies that managed to strike it rich in smartphones or Wii or some other specific application that took off. Guys like Kionix and InvenSense. They’re visible at conferences and they put a fair bit of energy into the marketing of their technology. In fact, to my mind, that’s one of the things that sets them apart: aggressive marketing.

Then there’s a long tail of companies that have been doing yeoman’s work deep in the caverns, with no IPOs or champagne sales conferences and scarcely a pat on the back. Each one has a particular niche or angle or variant on the technology. You might look at them and think they could do with a bit more sophistication, but the fact is, they’ve been scrambling for years on a shoestring, and fancy ad campaigns just haven’t been in the budget.

These are going to be make-or-break times for such companies, in my opinion. It’s like they’ve come up from the caverns, blinking in the sunlight, realizing that there’s a whole new environment in which to work, full of both promise and challenge. As MEMS gains legitimacy and becomes mainstream, the pressure is likely to grow on everyone to perform more like the more visible folks. Marketing becomes more important as messages get refined and cast farther afield. Granted, it’s a bit Catch-22, since you need the success to fund the marketing, but you need the marketing to achieve the success.

If this were EDA, everyone would be predicting the imminent demise of most of the little guys. But it’s not EDA, it’s MEMS, and MEMS seems to play by its own rules. But as more visible companies have their day in the sun, they’ll cast their shadows over the smaller folks, and so the managers in the long tail will have to work harder to prove their value.

As if they didn’t already have enough to do…

Guest Blog: New board from element14 features Xtrinsic sensors

(Originally posted by Michael E Stanley in The Embedded Beat on Jun 18, 2013.)

I returned from Sensor’s Expo last week to find a new toy waiting for me. element14 has released a new board for the Freescale Freedom development platform featuring Xtrinsic sensors. For those of you who may have been hiding under a rock for the last year or two, these development boards duplicate the header pinout of the popular Arduino hobbyist boards, but are based upon industry standard ARM technology-based MCUs. The new sensor shield by element14 (pictured on top of the FRDM-KL25Z Freescale Freedom development platform) includes three Xtrinsic sensors:

I have blogged on the first two sensors before (Xtrinsic pressure sensor/altimeter: Part 1, Xtrinsic pressure sensor/altimeter: Part 2 and Magnetic sensor makes electronic compass design easy).  I haven’t talked about the MMA8491, so it’s about time since it’s a really neat part. Unlike most other accelerometers, this little guy is designed to measure acceleration on demand, NOT based on some internal timer. The original target application was tamper detection. The device has 3 output pins which provide tilt detection at 45 degrees. Just toggle the EN enable line, and the X/Y/Z output signals are automatically updated. At 400nA per sample, this device has amazingly low power demands. And if your application does have a microcontroller, then just use the I2C port to read 14-bit sampled accelerometer values. That works out to be1mg/LSB sensitivity.

MMA8491 Block Diagram

element14 provides a 27-page user manual to take you through the paces of setting up and talking to your board. The board connects to your PC via a cable adapter from standard to mini USB. The board enumerates as a mass storage device, and element14 provides a precompiled command interpreter that can be downloaded to the Freedom development board via drag-and-drop from your PC desktop. The demo utilizes a virtual serial port over the USB line. You should be able to use almost any terminal emulator package to communicate to the board. My contact at element14 has used Termite and Teraterm Pro.  I used RealTerm.

Demo app streaming altimeter data

The screen dump above shows a sequence of MPL3115 altitude and temperature readings. You will notice 3 “altitude levels” at approximately 398, 397 and 396 meters. These correspond to me holding the board above my head (while seated), on my desktop, and on the floor of my office.  In other words, we’re seeing about two meters difference in height, as expected.

The MMA8491Q accelerometer can be sampled up to 800 times a second, and the MAG3110 has a max sample rate of 80Hz. So you’ve got enough bandwidth to implement an eCompass.  But the combination of sensors on this board work out really nicely for tamper detection, smart grid and smart metering applications as well.

The kit includes both sensor shield and KL25Z Freescale Freedom development platform and cost only $26.99.  You can order it now at