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 Effectively Test Controls with Real-Time Digital Twins and Automated Testing. Workflow Introductions Hardware-in-the-Loop Industry Use Cases
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
Electric Motor Controls with Simulink Design, prototype, and test your brushless DC motor controls using Simulink and Speedgoat hardware Reference Examples Rapid Control Prototyping Hardware-in-the-Loop
Simscape Vehicle Templates Run custom Simscape Vehicle Models in Real-Time Reference Examples Hardware-in-the-Loop
Lane Detection on FPGA Reference Example Learn how to perform hardware-accelerated vision processing for driver assistance and automated driving systems by implementing real-time lane detection. Reference Examples Hardware-in-the-Loop
Real-Time Simulation and Control of High-Performance All-Electric Autonomous Racing Cars Discover the full autonomous software stack from Technical University of Munich’s Roborace team. Designed with Simulink and ready to run on Speedgoat. Reference Examples Hardware-in-the-Loop Rapid Control Prototyping
Real-Time Driver-in-the-Loop Reference Example Learn how to create and run real-time virtual vehicles and Driver-in-the-Loop simulators to safely test and validate your new designs. Reference Examples Hardware-in-the-Loop Rapid Control Prototyping
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
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. 18 Nov 2021 Published Papers Hardware-in-the-Loop