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Collection of videos, reference examples, and more to support your real-time simulation and testing workflows

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Real-Time Simulation and Testing with Simulink Real-Time and Speedgoat Hardware

Real-Time Simulation and Testing with Simulink Real-Time and Speedgoat Hardware

Speedgoat real-time solutions and Simulink® are expressly designed to work together for creating real-time systems for desktop, lab, and field environments.

Workflow Introductions

Hardware-in-the-Loop

Rapid Control Prototyping

Hardware-in-the-Loop Simulation

Hardware-in-the-Loop Simulation

Effectively Test Controls with Real-Time Digital Twins and Automated Testing.

Workflow Introductions

Hardware-in-the-Loop

Industry Use Cases

Rapid Control Prototyping

Rapid Control Prototyping

Accelerate Control Design Innovation With Model-Based Design Ready Solutions for a Worry-Free Test and Simulation Experience.

Workflow Introductions

Rapid Control Prototyping

Industry Use Cases

Introduction to Speedgoat Simulink-Programmable FPGAs

Introduction to Speedgoat Simulink-Programmable FPGAs

Learn about the Simulink-integrated workflows to program FPGA I/O modules easily and directly from your model.

Workflow Introductions

Hardware-in-the-Loop

Rapid Control Prototyping

Timing and Synchronization

Timing and Synchronization

Connect distributed systems with multiple nodes and create deterministic real-time applications with Speedgoat timing and synchronization solutions.

 

How To

Update Target Operating System to R2020b and Later

Update Target Operating System to R2020b and Later

Simulink Real-Time R2020b and later releases ship with a QNX-based 64-bit real-time operating system (RTOS). Learn how to update the software of your existing Speedgoat real-time target machine running on R2020a or earlier.

How To

Part 1: System Configuration of Host PC (R2020b and later)

Part 1: System Configuration of Host PC (R2020b and later)

Learn how to set up the host computer for smooth operation, test the host-target communication and troubleshoot basic installation issues.

How To

Part 2: Configuration of Target Machine (R2020b and later)

Part 2: Configuration of Target Machine (R2020b and later)

Understand the operating principles of real-time target machines, learn how to configure your target machine and create and transfer a Simulink Real-Time™ kernel.

How To

Part 3: Running Real-Time Applications (R2020b and later)

Part 3: Running Real-Time Applications (R2020b and later)

Understand the main principles of real-time simulation. Configure and prepare Simulink® models for real-time execution. Deploy Simulink® models as real-time applications onto Speedgoat target machines.

How To

Part 4: Data Logging (R2020b and later)

Part 4: Data Logging (R2020b and later)

Monitor, visualize, and log signals using the Simulation Data. Inspector (SDI) on the development computer. Write data to the disk of the target machine using “File Scope” blocks.

How To

Part 5: Control and Instrumentation (R2020b and later)

Part 5: Control and Instrumentation (R2020b and later)

Learn how to use a Simulink® model as a direct user interface to the real-time application. Tune parameters using MATLAB command lines to control the execution of the real-time application. Create custom user interfaces using MATLAB App Designer.

How To

How to Configure a Speedgoat Test System for Simulink Real-Time

How to Configure a Speedgoat Test System for Simulink Real-Time

Configuring your Speedgoat machine for Simulink Real-Time: A Step-by-Step Guide

How To

Speedgoat Configurable I/O Modules

Speedgoat Configurable I/O Modules

Learn about the Simulink-integrated workflows to configure I/O modules easily and directly from your model.

Workflow Introductions

Hardware-in-the-Loop

Rapid Control Prototyping

Designing a Generic, Software-Defined Multimode Radar Simulator For FPGAs Using Simulink HDL Coder and Speedgoat Real-Time Hardware

Designing a Generic, Software-Defined Multimode Radar Simulator For FPGAs Using Simulink HDL Coder and Speedgoat Real-Time Hardware

This publication focuses on the implementation and testing of a fully-parameterized radar signal processing prototype. A Speedgoat Performance machine with two Simulink-Programmable FPGA I/O modules IO342 are used for the implementation of a radar signal processing design containing several common waveforms and tunable parameters and a radar scene generator for delay, doppler, and amplitude measurement.This setup helped increase the simulation fidelity while reducing the time to test.

Published Papers

Design, Simulation and Hardware-in-the-Loop (HIL) Testing of an Electric Scooter Powertrain

Design, Simulation and Hardware-in-the-Loop (HIL) Testing of an Electric Scooter Powertrain

This publication focuses on an algorithm to control a brushless DC motor. A Speedgoat performance machine runs a digital twin of the motor on both the CPU and the FPGA-based I/O module IO334 and is connected via the analog channels to the controller, an MCU by Texas Instruments. With this HIL setup, the performance of the control algorithm was tested. 

Published Papers

Hardware-in-the-Loop

Certification Process for a Hybrid Electric Aircraft

Certification Process for a Hybrid Electric Aircraft

The scientific aviation association (FVA) is developing the FVA 30, a hybrid electric motor glider, to research alternative propulsion systems. This article focuses on the certification process of the FVA 30 power train, using a Speedgoat target computer.

Hardware-in-the-Loop

Published Papers

Battery Management System Integration into an Electronic Control Module for a Hybrid Electric Aircraft

Battery Management System Integration into an Electronic Control Module for a Hybrid Electric Aircraft

Th­is article focuses on BMS integration into the electronic control module (ECM) of the FVA 30 hybrid electric motor glider using a Speedgoat real-time target machine. The challenge is to design an ECM for reliable data processing, allowing pilots to monitor and control the drivetrain.

Published Papers

Rapid Control Prototyping

Assessment of State-of-Charge Estimation Method for Lithium-Ion Batteries

Assessment of State-of-Charge Estimation Method for Lithium-Ion Batteries

In this paper, a numerical model of lithium-ion batteries is developed and deployed to a Speedgoat Baseline target machine. The estimation method for the state-of-charge (SOC), based on a nonlinear autoregressive with exogenous input (NARX) and artificial neural networks (ANNs) that are correctly trained with multiple datasets, is designed, and experimentally validated by hardware-in-the-loop simulation.

Publication on mdpi.com

Published Papers

Hardware-in-the-Loop Testing (HIL) of State-of-Charge (SoC) Estimation for Li-Ion Batteries

Hardware-in-the-Loop Testing (HIL) of State-of-Charge (SoC) Estimation for Li-Ion Batteries

This study presents the design and validation of an SoC estimation method for lithium-ion batteries in hybrid-electric vehicles (HEV). The battery model is deployed on a Speedgoat Baseline machine connected to a Raspberry Pi emulating the ECU based on an artificial neural network for HIL testing. The algorithm can estimate the SoC of the battery with 2% accuracy during real-time testing.

Published Papers

Hardware-in-the-Loop

Vorticity Dynamics of Leading-Edge Vortex Formation on a Revolving Wing

Vorticity Dynamics of Leading-Edge Vortex Formation on a Revolving Wing

A leading-edge vortex (LEV) forms and remains stably attached on high angle-of-attack (AoA), low aspect ratio (AR) wings undergoing revolving or flapping motion at an insect’s wing. Here, the LEV formation on a revolving wing is investigated. The 'Shake-the-box' (STB) Lagrangian particle tracking velocimetry (PTV) system and a volumetric patching process helped reconstruct the entire time-resolved flow field.

Publication on springer.com

Published Papers

Part 1: System Configuration of Host PC (R2020a and earlier)

Part 1: System Configuration of Host PC (R2020a and earlier)

Learn how to set up the host computer for smooth operation, test the host-target communication and troubleshoot basic installation issues.

How To

Part 2: Configuration of Target Machine (R2020a and earlier)

Part 2: Configuration of Target Machine (R2020a and earlier)

Understand the operating principles of real-time target machines, learn how to configure your target machine and create and transfer a Simulink Real-Time™ kernel.

How To

Part 3: Running Real-Time Applications (R2020a and earlier)

Part 3: Running Real-Time Applications (R2020a and earlier)

Video tutorial series part 3: Understand the main principles of real-time simulation. Configure and prepare Simulink® models for real-time execution. Deploy Simulink® models as real-time applications onto Speedgoat target machines.

How To

Part 4: Data Logging (R2020a and earlier)

Part 4: Data Logging (R2020a and earlier)

Monitor, visualize, and log signals using the Simulation Data. Inspector (SDI) on the development computer. Write data to the disk of the target machine using “File Scope” blocks.

How To

Part 5: Control and Instrumentation (R2020a and earlier)

Part 5: Control and Instrumentation (R2020a and earlier)

Learn how to use a Simulink® model as a direct user interface to the real-time application. Tune parameters using MATLAB command lines to control the execution of the real-time application. Create custom user interfaces using MATLAB App Designer.

How To

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