In the current highly competitive business environment, product development processes are becoming increasingly complex as products become customized. The complexity of such systems leads to an inability for analysis by using mathematical methods or to allow realistic models to be evaluated analytically; as such these models are imperative to be studied through the means of simulation. Design simulation helps manufacturers verify and validate the intended function of a product under development, as well as the manufacturability of the product. Several design simulation approaches have become standard components of product development in many industries, and they continue to grow in importance as inexpensive, faster computers and affordable, easy-to-use design simulation software allow users to address new technologies and applications.
As opposed to trial-and-error, a smart simulation process allows targeted implementation of design choices in various stages of the development cycle. This is ultimately benefiting the design engineers and the company by reducing extra expenses and less work when it comes to applying on the real systems.
Our ELE Times correspondent Sheeba Chauhan took this opportunity to interact with Bob Williams, managing director of Pulsonix, and R Vijayalayan, Manager, Automotive Industry Field Application Engineering Team of MathWorks. This conversation turned an extra mile as it covers some very interesting recent launches in the market.
Different ways of design & Simulation tools supporting in high frequency electronic designs
Bob Williams, MD of Pulsonix commented that the design system tools manage and support frequencies ranging from low to high frequency. Dedicated toolsets provide the user with specific functionality ranging from technology management to the actual physical manual routing tools where the design can be hand-crafted to match track pattern requirements. With tight integration to Spice simulation, users can use the same library and Schematic capture tools to create blocks of circuitry that can be simulated, such as in the case of the Pulsonix tool. This tight integration and use of the library mean one design tool can be used with the elimination of possible user error and data conversion factors. Other software tools such as signal integrity and power integrity simulation products add layers of sophistication to the design process. These will be utilised when speed of the design becomes an issue or where impedance of both the design and layer structure is paramount.
In further conversation with R Vijayalayan, Manager, Automotive Industry Field Application Engineering Team, MathWorks, he stated that Modern RF systems consist of high-frequency analog electronics (the front end) and adaptive digital algorithms. One of the primary challenges in RF system design is reducing the overall area, power, and cost for RF front ends—generally wireless transmitters and transceivers. For this reason, smart RF system design relies heavily on compensating DSP algorithms, adaptive filtering, and control logic to optimize these performance factors and to calibrate and compensate for RF impairments.
Algorithms such as digital pre-distortion (DPD), automatic gain control (AGC), beamforming, and adaptive filtering are an integral part of today’s communications and radar systems. RF system algorithms, such as the ones required by emerging 5G systems, need to be designed together with models of the antenna front end, analog/mixed-signal components, and the communication channel.
Design & simulation tools-Reducing the risk factor of error in the development process
R Vijayalayan responded that organizations are successfully addressing the challenges of fast-evolving market needs and increasingly complex system design by adopting Model-Based Design in place of traditional waterfall methods. Model-Based Design provides a mathematical and visual approach to develop complex systems. The systematic reuse of models is a basic principle of Model-Based Design, where models form a digital thread connecting development, design optimization, code generation, and verification and validation. MathWorks tools use simulation testing and formal methods-based static analysis to complement Model-Based Design with rigor and automation to find errors earlier and achieve higher quality.
Talking of same Bob Williams said, there will always be an element of trial and error but the use of electronic simulation means this is drastically reduced without the need for traditional breadboarding and prototyping which can be costly, time-consuming and error-prone. By using the Schematic tool as the ‘master’ and utilising the same libraries that will ultimately be used for the PCB, there is only ever one management tool and library set which reduces errors and speeds up the design process.
The latest design tools along with the applications
Pulsonix have the EDA CAD tools, functionality is developed to cater for the simulation tool advances. Better integration and a higher usability of the EDA tools ensures users are kept in-line with technology advancements. In terms of applications and frequencies, the variety is endless. Ranging from small RF projects to full high-speed designs, each application has different demands on the tools and simulations required, be it Spice, Signal Integrity or Power Integrity etc.
While Mathworks have different tools to offer- RF PCB Toolbox: RF PCB Toolbox provides functions and apps for designing, analyzing, and visualizing high-speed and RF multi-layer printed circuit boards (PCBs). With RF PCB Toolbox, designers of RF boards, modules, MMICs, and SiPs can predict PCB performance and verify that the manufactured PCB meets specifications. For RF and antenna designers, the toolbox provides parameterized models of distributed filters, couplers, splitters, matching networks, and Gerber file generation. Toolbox support for ODB++ and databases from Cadence Allegro, Mentor Expedition, Altium, and Zuken enables signal integrity engineers to analyze the high-speed portions of the PCB layout.
Signal Integrity Toolbox: Signal Integrity Toolbox provides functions and apps for designing high-speed serial and parallel links. Signal Integrity Toolbox lets the engineers analyze waveforms and eye diagrams and measure channel quality while observing effects such as ISI, jitter, and noise. They can analyze the channel in the frequency domain for insertion loss, return loss, and crosstalk, and verify compliance with industry standards including IEEE 802.3, OIF, PCIe, and DDR.
Satellite Communications Toolbox: As the number of low earth orbit (LEO) satellites increases to serve the high-speed mobility market, Satellite Communications Toolbox is designed to help equipment makers and operators model, simulate, analyze, and verify satellite communications systems and links.
Along with this, they have Radar Toolbox and DDS Blockset which are equipped with present technology to perform faster.
The benefits of Design & Simulation tools
Bob Williams responded that the benefits are tremendous for engineers, and the company overall. After design, product prototypes and finally the product themselves, the benefit from an up-front design simulation that has gone most of the way to verifying the design is surmountable. Other than real-world issues such as EMC/EMI and other unforeseen circumstances, the tools available for simulation and EDA design create an environment where not only is time saved, but the accuracy of being able to design and verify within a software structure can only be productive.
R Vijayalayan supported his responses with some practical examples and said that with the need for efficiency improvement and meeting shrinking timelines, there’s a big need for virtualization of the system development and testing using the simulation-based approach. Engineers and scientists are looking for ways to perform multidomain modelling and simulation, because you can reuse models across environments to simulate how all parts of the system work together. Simulink enables you to design your system with multidomain models, simulate before moving to hardware, and deploy without writing code. Simulink has been used by engineers and scientists across the world to derive many benefits including:
- Modeling systems across domains using specific tools and prebuilt blocks.
- Developing large-scale models through componentization with reusable system components and libraries.
- Combining models into one system-level simulation even if they weren’t built in Simulink.
- Running massive simulations in parallel on your multicore desktop, computer cluster, or the cloud, without writing lots of code.
- Sharing simulations as standalone executables, web apps, and Functional Mockup Units (FMUs)
Upcoming technology in the design & Simulation
Bob Williams responded that power and thermal integrity tools have probably been the most developed in recent times with the need to simulate ‘what-if’ scenarios where boards have become more miniature in size but the devices are power hungry and hence, hot! Spice simulation for everyday electronics is still the mainstream go-to requirement with signal integrity simulation a prerequisite for high-speed designs where impedance control and impedance-defined layers stack-ups are required.
Talking of the same R Vijayalayan said Electrified vehicle development requires one to address many challenges in parallel such as Total vehicle efficiency, new engineering capability – power electronics, high-voltage battery, motors, embedded software quality and transition from prototyping work style to production mind-set and processes. MathWorks helps engineers tackle these challenges through a unified design environment for system engineering, software engineering, and data science.
With the increase in software content in today’s vehicles, companies are turning toward virtual vehicles to test their software as soon as possible. Using simulation, they can assemble all the key software components that have to work together for a specific application and study how well they meet their requirements. Virtual Vehicle also enables engineers to assess functional behaviour and gain insight while reducing time spent in the vehicle, especially when the test cases have any hazardous scenarios.
This approach coupled with data analytics enables engineers to use the simulation models of vehicles or automotive systems as virtual dynos/vehicles. This helps in performing virtual testing or calibration that results in savings of time and cost. The need of the hour is to translate human expertise into a systematic and repeatable framework for testing and calibration that can produce consistent results and be reusable across multiple programs by enabling the engineers to perform most of the tasks at their computer.
Contributing Authors:
Sheeba Chauhan | Sub Editor | ELE Times
