Altair's CAE Portfolio for IoT Product Design
Shawn Wasserman posted on September 19, 2016 |
Design challenges for IoT devices will often require engineers on CAE tools to discover solutions. (Image courtesy of Altair.)

Design challenges for IoT devices will often require engineers on CAE tools to discover solutions. (Image courtesy of Altair.)

Connected devices on the Internet of Things (IoT) will invariably be more complicated for engineers to design than their “dumb” product counterparts.

“Designing a smart IoT product is not as simple as adding a chip or assigning an IP address, and saying it is connected,” joked Vincent Marchè, marketing director at Altair. “Designers are challenged to achieve reliable communication in any conditions while limiting energy consumption or self-powering the device.”

For instance, adding an antenna for the IoT connection could theoretically affect other aspects of a product, or other products in the area, that operate on the electromagnetic (EM) spectrum. This EM compatibility (EMC) issue is just one way that IoT engineers can find themselves reevaluating design criteria.

The challenges for IoT product designers don't end there. Marchè added that these engineers need to ensure the product is compact, lightweight, affordable and robust enough to survive in various environments.

Clearly, meeting these design challenges is a multidisciplinary project. To tackle these challenges, IoT design teams will need to use a multitude of computer-aided engineering (CAE) tools that can handle complex multiphysics and multidisciplinary problems to ensure that products get to market on time. Dealing with these multiple licenses can become expensive and complicated.

The solution many CAE vendors have come up with is token-based licensing where engineers buy tokens which can be used to gain access to multiple tools and resources. For Altair, that comes in the form of HyperWorks Units (HWUs). HWUs can also help to ensure that the cost of operating all of these design tools will not stack

Protect IoT Devices from Ghostly Possessions with EM Compatibility

When products experience poor EM compatibility, a lot of issues may arise that will look rather “spooky” to the user. For instance, electronic doors may not open when commanded and odd noises might come from speakers or captured by recorders. If these ghosts in the machine don't scare the user, they are sure to annoy them. These EM compatibility gremlins may also become more than just a nuisance if the issue affects advanced driver assistance systems(ADAS) or Industrial IoT (IIoT) equipment in factories.

EM simulation of a printed circuit board (PCB) with a ZigBee antenna (left) and simulation of a near field RFID antenna mounted on a forklift. Simulations detect EM issues like interference and blindspots.(Image courtesy of Altair.)
EM simulation of a printed circuit board (PCB) with a ZigBee antenna (left) and simulation of a near field RFID antenna mounted on a forklift. Simulations detect EM issues like interference and blindspots.(Image courtesy of Altair.)

“Companies developing IoT products and systems need to ensure their designs fulfill all the required EMC standards and regulations so to ensure such systems work correctly when they operate together,” clarified Marchè. “An IoT device should not interfere with another system but at the same time be immune enough to external interferences so as to continue operating normally.”

Marchè explained that engineers designing IoT products might create a wireless module that exceeds the maximum electromagnetic emissions allowed for EMC standards. These EM emissions would lead to the haunting possessions that afflict electronic devices.

To bust these ghosts, Marchè suggests that simulation tools such as FEKO be used to design shielding, which will reduce the EM emissions from IoT modules or surrounding cables.

“Software like FEKO has many features that make it suitable for a variety of EMC and EMI simulations.  These features include specialized techniques for calculating extremely high shielding values and advanced cable modeling techniques,” said Marchè.  

Maximizing the Range of an IoT Device's Antenna

A similar problem to the EM compatibility of products is maximizing the IoT device's antenna range.

“The performance of an antenna can significantly change depending on its environment,” said Marchè.“Two of the main parameters of an antenna directly affecting the communication range are the radiation pattern and the antenna gain. The radiation pattern and gain of an antenna in a wireless sensor can change depending on where and how such a sensor is mounted and installed.”

Engineers can use FEKO to design the antenna and assess how it will operate within its environment. This will allow for the maximization of the IoT device's communication range.

To get a better idea of the wave propagation of the communication device, users can also look into WinProp. This wave propagation modeling tool allows engineers to model wireless sensor networks with various nodes.

“Essentially, one can simulate and analyze the connectivity and path losses between the nodes of the network in different environments: rural, urban and indoor,” said Marchè. “[WinProp can assess] different wireless air interfaces while considering other aspects like interferences and probability of failures for the nodes.”

By maximizing the range of IoT devices, the end user will need to worry less about how to integrate various IoT devices within a large space like a factory or a power plant.

Proximity sensor designed in Flux 3D. (Image courtesy of Altair.)

Proximity sensor designed in Flux 3D. (Image courtesy of Altair.)

IoT Device Energy Management Is a Multidisciplinary Problem

One of the biggest challenges with creating an IoT device is ensuring that the device will wirelessly operate independently for long periods of time. To meet this requirement, engineers will need to optimize the energy management of the device.

Sure, the device can utilize a rechargeable battery, but that means the user will need to physically interact with the IoT device on a regular basis. This maynot be feasible for devices in remote or hard-to-reach locations.

One solution to this problem is to design self-charging devices. These devices will harness the energy from their surroundings through lights, rotations and vibrations. Think of an IoT traffic light coupled with a solar panel, or an industrial sensor that charges its battery from the vibrations of the machine it is monitoring.

System simulation of a robot within Embed.(Image courtesy of Altair.)
System simulation of a robot within solidThinking Activate.(Image courtesy of Altair.)

Marchè suggests that engineers can use various products offered by Altair to meet the CAE requirements to design these self-sufficient IoT devices. These tools include:

  • Flux for electromagnetic studies and component energy optimizations of actuators and motors
  • Compose (matrix based), Activate (block diagram based) or Embed (model based) system simulations to maximize the energy flow of the system
  • OptiStruct (finite element analysis) or AcuSolve (computational fluid dynamics) to limit mechanical and heat losses that drain power
Dashboard of IoT data collected and processed in Envision. (Image courtesy of Altair.)

Dashboard of IoT data collected and processed in Envision. (Image courtesy of Altair.)

What to Do with All That IoT Data

For IoT engineers, the design of a connected product doesn't end when it's on the market.

Using tools like solidThinking's Envision, engineers can process the data collected on the IoT into dashboards. This data can then be monitored in real time to make informed decisions on the fly. Additionally, this information can also be fed back into the development cycle once new use cases and updated environmental data are discovered.

“Increasing the amount of sensors will enable IoT devices to generate much more data, shared within a defined community, capable of mobilizing reliable statistics,” said Marchè. “The quality of this data will contribute to more efficient decisions and predictive algorithms, which should enable engineers to make pre-emptive decisions before situations happen: avoiding collisions, planning preventive maintenance works and more.”

In other words, the challenge of designing an IoT product never really ends. The data collected by these connected devices are invaluable to engineers looking to update the next iteration of the product or maximize the performance of a current product in the field. But one thing is for sure, the information you gather will be invaluable and teach you things about your product you never knew like new use cases and loads affecting the design.

To learn about other ways Altair can help engineers optimize their IoT designs, read: Internet of Things: Value, Waves, and More.

Altair has sponsored to write this article. It has provided no editorial input. All opinions are mine. —Shawn Wasserman

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