Seven Crucial Applications to Successfully Engineer the Internet of Things

BY ANSYS

The internet of things and the products and devices that make it work are incredibly complex, consisting of everything from mammoth data centers to tiny solder balls on a chip. Each component and subcomponent is affected by the other components and the environment in which each operates. Seven applications, enabled by simulation, are critical to cost-effective and timely development of iot products.

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Three elements of the IoT

In its simplest form, the Internet of Things (IoT) comprises three elements: the things, the network or gateway, and the cloud. Things, such as cars, phones, robots, industrial equipment and even homes, are becoming smart and connected. More and more processing power is being added to these things. The network is integral to the IoT infrastructure; without it there are no connected devices. A robust and reliable network includes high-speed routers, switches and gateway technology. The cloud consists of data centers and the software that runs much of the business logic of the IoT.

Each product or device that makes up these three elements is in itself a collection of components that must work together reliably. Components, both electronic and structural, include integrated circuits, switches, antennas, sensors, batteries, cases and much more that in turn make up larger components and complete systems. The complexity is astounding. Each component must work as intended by itself, as part of the complete system of components and within operating environments that are often harsh and sometimes unexpected.

Studies have shown that designing products of this complexity through an integrated simulation platform is much superior to physical testing or performing simulation in silos. This integrated platform enables seven applications in which simulation is essential to designing successful products for the IoT. ANSYS provides not only a best-in-class platform but proven tools that reduce costs, increase reliability, and speed time-to-market for each of these applications.

"Synapse uses ANSYS HFSS and the ANSYS human body model to evaluate performance of various antenna designs by modeling the complete system, including the wireless device and antenna and their interactions with the human body."
— SYNAPSE PRODUCT DEVELOPMENT

ANTENNA DESIGN AND PLACEMENT
Simulation of donut-shaped radiation pattern of a dipole antenna 
 
Simulation of donut-shaped radiation pattern of a dipole antenna

Antennas are essential for the things within the IoT to communicate with each other reliably. Without antennas, the IoT would not exist. Wireless systems that are prototyped and tested in anechoic chambers can experience issues with multipath signal propagation and fading once integrated into a device. The structure of the device itself — be it a manufactured object or a human body — as well as motion and other environmental factors can cause the antenna to fail or not perform optimally. To provide rich functionality, modern devices may use a combination of wireless technologies — Bluetooth®, Wi-Fi, LTE — that require multiple antennas. Antenna coupling and co-site issues can degrade performance. For example, a wireless sensor network deployed in a factory contains sensors with dipole ANTENNA DESIGN AND PLACEMENT antennas to communicate with other sensors. The ideal radiation pattern of a dipole antenna resembles a donut, but, when deployed in the industrial setting, the complex structures and interference from other antennas distort the radiation pattern, reducing antenna efficiency, increasing power consumption and leading to unreliable performance and failure.

ANSYS provides solutions to predict the effects of the entire industrial environment on the performance of antennas and wireless devices. This approach provides greater insight, improves accuracy and increases reliability.

POWER MANAGEMENT

chip-package co-analysis
 
Chip–package co-analysis

Designing high-speed printed circuit boards (PCBs) and semiconductor integrated circuits (ICs) that make up devices, networks and data management for the IoT poses significant challenges. Engineers must address the complexity of designing for lower operating voltages, increasing circuit density and faster data rates. Engineers must balance the requirements of three broad areas that affect product reliability — electrical, thermal and mechanical performance. They also need to simulate the interactions between the IC, the IC package and the PCB.

Electrical reliability requires engineers to perform signal- and power-integrity analysis. Power integrity simulations ensure that power delivery networks are robust, and signal integrity analysis minimizes crosstalk and electromagnetic interference (EMI). Addressing thermal reliability entails simulation to evaluate the impact of board temperatures and associated components so that devices operate reliably in the specified operating range. Mechanical reliability requires a thermal stress simulation to evaluate thermal and mechanical stresses in the board, as well as solder joints between board and components.

In addition to individual physics simulations, engineers must consider the interaction between physics disciplines, coupling electromagnetic field simulation with thermal simulations and connecting thermal simulations with structural analysis. This method provides a holistic view of the overall reliability of the PCB design.

The chip–package–system workflow, unique to ANSYS, enables engineers to improve electronic system performance. With all relevant systems-level considerations modeled and simulated, engineers can reduce electromagnetic interference, develop robust electrostatic discharge (ESD) protection, and improve electronic systems to power the IoT economy.

POWER MANAGEMENT
Wireless communication 
 
Wireless communication

Anyone whose smartphone battery has run out understands the essential role of power management. But power management isn’t just about smartphones or Wi-Fi. Energy harvesting, wireless power transfer and low power IC design are the foundations on which many IoT devices will be built.

Energy from mechanical motion, heat, piezoelectric material and electromagnetic emissions can be captured and converted directly into electricity. When designing energy harvesting systems, engineers need to consider several parameters, including the energy source, transducer type, power efficiency, required power levels and energy storage. ANSYS provides a wide range of simulation tools that work seamlessly together to take all these factors into consideration.

When designing wireless systems, safety is a key consideration. Standards and regulatory agencies limit the amount of electromagnetic energy that can be delivered to living tissue. ANSYS simulation tools, including human body models, can be used to design and analyze a variety of power delivery systems and their impact on the human body.

SENSORS AND MEMS DESIGN
Gyroscope simulation 
 
Contours of z-axis deformation on a gyroscope

Sensors, actuators and other MEMS (microelectromechanical systems) devices are essential to the IoT. They gather the information from the environment necessary for human–machine interfaces, device management and product feedback; trigger action based on that feedback, such as starting or stopping heating systems, showing a warning, or opening a valve; and perform a whole host of other functions. Designers of sensor and other MEMS devices face business and technology challenges when designing, prototyping and creating compelling products that can mean the difference between success and failure. To gain a competitive advantage, MEMS manufacturers need to develop their products as fast and efficiently as possible.

MEMS and sensors are complex because of their special functions, challenging manufacturing processes and often tiny size. MEMS devices are so small that performance measurement equipment can impact device function, making it difficult to obtain reliable performance data. Simulation provides accurate insight into the performance of these devices beyond what physical prototyping affords.

ANSYS solutions enable simulation of a wide range of sensors, actuators and other MEMS devices, from RF sensors dependent on electromagnetic fields to gyroscopes dependent on mechanical motion to piezoelectric devices that depend on both mechanical and electromagnetic components. Proven solvers and coupling solutions enable high-fidelity analysis of device designs. Once an initial design is created and simulated, ANSYS tools allow the entire device to be optimized before physical prototyping, including how the components will work together and transmit their information.

EMBEDDED SOFTWARE DEVELOPMENT

Autonomous vehicle 
 

Many modern cars contain 50 to 100 million lines of code. With autonomous vehicles on the way, software content will rapidly increase. But it is not just cars: Software is essential to adding richness and smart functionality to many IoT devices, including industrial equipment, robots, planes and drones. Because many of these products and systems are safety- or mission-critical — for example, braking systems on cars and planes — the control software must operate flawlessly. When systems fail, they must fail in a predictable way to minimize damage.

Industry regulations, certifications and qualifications often govern the reliability and performance of software. Software development is no longer just about writing the code: It is about verification and validation. For each line of implementation code, software engineers often find themselves writing many more lines of verification code. Despite the amount of effort expended, software code bugs continue to persist, leading to safety recalls, security breaches and sometimes tragic outcomes.

ANSYS has created a model-based embedded software development and simulation environment with a built-in automatic code generator that significantly accelerates the pace of embedded software development projects. Engineers can use ANSYS solutions to model complex systems, understand the interaction of various subsystems, and generate high-integrity software code that complies with industry standards. The ability to generate millions of lines of code at the push of a button not only removes human coding errors, but also increases productivity, quality and traceability of code.

Automatic code generation using ANSYS software modeling tools enables engineers to express the design specification in a formal manner. As a result, companies can produce software with a significantly reduced certification cost and reduce the number of very expensive test demonstrations. Software modeling and simulation can reduce software generation time, providing a time-to-market advantage.

DESIGNING FOR HARSH ENVIRONMENTS
Belt clip simulation 
 
Designers used ANSYS simulation tools to optimize this wearable device belt clip for strength, fatigue life and thickness.

Whether they are employed in industrial, aerospace or consumer applications, IoT devices can be subjected to harsh environments including vibrations, impact and fatigue. Despite these conditions, IoT devices must be robust and remain active for extended periods and across great distances without maintenance. In these extremes, a malfunction can result in significant investment to repair or replace the system, mission failure, and even risk to human lives. NASA has shown that 45 percent of first-day spacecraft electronics failures were due to damage caused by vibrations during launch.

Engineers must consider these potential harsh environments very early in the development process when design choices can be made at the lowest cost — and with the least impact on the project schedule. Physical prototyping is simply not a viable option for many obvious reasons. Not only is it difficult to create all the possible test scenarios given the constraints of time, budget, location and resources, but also the measurement results can vary greatly and lack the fidelity needed for IoT and many other critical applications. One leading aerospace and defense firm simulated harsh environmental conditions, including vibration, to eliminate expensive destructive testing. As a result, they were able to save over $1 million by reducing the development time, eliminating consultant fees, reducing physical testing, improving product capabilities for accuracy and maintaining safety.

VIRTUAL SYSTEM PROTOTYPING
Advanced driver assistance system - ADAS 
 
An advanced driver assistance system (ADAS), common in today’s cars, requires both electromagnetic and systems simulation to develop.
Image courtesy ESSS.

As product complexity grows, so does the need for enhanced simulation capabilities. The complexity within systems arises from the challenges of connecting the individual pieces to ensure that they work together as specified and expected. Coupling physical attributes of a product with systems and embedded software enables companies to greatly minimize integration issues, reduce costs, increase the likelihood of first-pass success and ensure that products perform as expected.

While it is easier to visualize the IoT in terms of individual devices or components — a smartphone, a thermostat or a wind turbine — the complex and invisible networks that connect them, as well as the cloud that stores and delivers data on demand, require sophisticated modeling and simulation. The smart wind turbine, for example, needs to adjust its behavior according to wind patterns, the amount of energy on the grid and the behavior of other smart wind turbines. To model the complete operation of this wind turbine and its interactions with the real world, engineers need to use simulation tools that model fluid dynamics, embedded software, and structural and electronic functions.

The interactions of the software, the electronics hardware and the multidomain nature of the problems significantly increase the complexity of the engineering challenge. Simulation software from ANSYS can help by providing validation results that include systems-level qualities, properties, characteristics, functions, behavior and performance insight. Based on this high-level perspective, system designers can make informed design choices that optimize the performance of not only each individual component, but also the entire system.

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