Demo Stations

Attendees who visit the demo stations are able to discuss their challenges and ideas with MATLAB® and Simulink® experts and see demos showcasing the latest features, including those described below.

Modeling System Architectures with System Composer

System Composer™ enables the definition, analysis, and specification of architectures and compositions for model-based systems engineering and software design. Learn and discuss how you can use System Composer to allocate requirements while refining an architecture model that can then be designed and simulated in Simulink.

Software Development: Enable Shift-Left in DevOps with Polyspace

DevOps enforces early verification on the software to ensure robustness and quality faster in the software development lifecycle. Discover and discuss how Polyspace Bug Finder™ and Polyspace Code Prover™ analysis enables the early detection of coding metrics like HIS metrics, coding standard violations like MISRA, and programming errors like division by zero. Understand how Polyspace allows software development teams to automate, learn, and get faster feedback for verification and result review workflows.

Motor Control with Systems on a Chip

From simulation models to systems on a chip (SoCs), see the implementation of a motor regulation algorithm on a heterogeneous SoC made of an FPGA and an ARM processor through IP core generation workflows and automatic HDL and C-code generation. This field-oriented control of a permanent magnet synchronous machine demo targets the Trenz® TE0820 SoM motor control kit with an AMD® (Xilinx®) Zynq® UltraScale+™ MPSoC module.

Visit this demo booth to see and discuss how MATLAB, Simulink, and HDL Coder™ are used to:

  • Reduce dependency on hardware with simulation
  • Perform faster hardware iterations with automatic deployment
  • Reuse your testbench throughout the development stages, from algorithm to deployment

Driver-in-the-Loop Virtual Electric Vehicle

Virtual vehicles can be used in many different ways throughout the design cycle. Here we highlight a workflow where one goes from raw racetrack data (inner and outer bounds) to a driver-in-the-loop simulation. To achieve this, we followed several steps: We provided the inner and outer bounds of the racetrack to a MATLAB script that fetches the elevation data and exports it to RoadRunner, where one can create an Unreal® scene; used the Virtual Vehicle Composer app to create a baseline electric vehicle; modified this vehicle to run on a Speedgoat® hardware-in-the-loop system; and added the hardware steering wheel and pedals input.

3D Scene and Scenario Creation in RoadRunner for ADAS Applications

Realistic virtual environments are a vital component in the workflow of advanced driver-assistance system (ADAS) function development. Learn and discuss how to create 3D scenes and scenarios with the RoadRunner suite to be used for simulations. Import and export data in various formats, populate the environment with assets from RoadRunner Asset Library, and cosimulate with MATLAB and Simulink for algorithm development.

Improve Quality and Comply with ISO 26262, ISO 21434, and ASPICE Standards

Early verifications on the model level and, later, on the code level to ensure model and code correctness are strategic activities within Model-Based Design. Learn and discuss capabilities such as model checking, coverage measurement, requirements management, and static analysis at the code level to increase the quality of your design. Understand how Model-Based Design with MATLAB and Simulink supports you in achieving compliance with standards for functional safety (ISO 26262), cyber security (ISO 21434), and Automotive SPICE (ASPICE) and guidelines such as MISRA. Additional benefits of implementing a mature issue detection process that identifies issues before going into production are high-quality software and contributing to the principles and metrics of DevOps or SAFe.