Knowledge Center

Flanders Make

Development of a High Precision Vehicle Drivetrain Test Bench.

GreenTeam

Formula Student racing success achieved through powertrain innovation.

Mobileye

Driving technology towards a fully autonomous vehicle.

Stanford University

Reducing emissions with low-carbon fuels.

ZKW Lichtsysteme GmbH

Developing Intelligent Lighting Systems for the Next Generation of Vehicles.

Incova

Designing intelligent valve-control system for a 20 ton excavator

Nuvera

Reducing commercial vehicle emissions using hydrogen fuel cells.

Ponsse

Cutting development time for harvester control software by at least a year with model-based design.

Tata Motors

Developing autonomous driving software including sensor perception, motion planning, and vehicle control algorithms.

Volvo

Equipment streamlines product development with a real-time, Human-in-the-Loop Simulator.

HIL Testing of BMS using Simulink Real-Time and Speedgoat target hardware

This webinar will demonstrate how engineers can perform hardware-in-the-loop (HIL) testing to validate and test their Battery Management Systems design using Simulink Real-Time^TM and Speedgoat Target hardware.

Rapid Control Prototyping for Power Electronics Control Design

This recorded webinar shows how power electronics control engineers can use rapid control prototyping (RCP) with Simulink Real-Time™ and Speedgoat real-time target machines to validate Simulink^® algorithms against electric motor and power converter prototype systems.

Accelerate Development of Power Systems with Real-Time Testing

This webinar will present how real-time solutions are being used to accelerate electric power generation, renewable energy integration, and onboard systems development. It highlights how Speedgoat real-time solutions enable electrical and control engineers to develop, test, and validate their innovations with hardware prototypes.

HIL and Automated Testing Applications for Aerospace

This recorded webinar presents how hardware-in-the-loop (HIL) testing is used to develop, test, and validate new aircraft components or systems such as controllers for aileron actuators. 

Advancing Electrification with Real-Time Testing

This recorded webinar presents how you can leverage real-time solutions to accelerate renewable energy integration and electric vehicle developments.

Independent Generation of Sequence Elements by Motor Cortex

Rapid execution of motor sequences depends on fusing movement elements into cohesive units that are executed holistically. The contribution of the primary motor and dorsal premotor cortex to this ability is determined in this paper. Also, the hypothesis that movement elements fuse makes specific predictions regarding three forms of activity, preparation, initiation, and execution is investigated.

Publication on nature.com

Developing and Testing Next Generation Control Systems

Learn how Speedgoat enables you to prototype and test complex control algorithms using full-vehicle simulation. By building a virtual environment for safe and realistic testing and verification, you can reduce prototype testing costs.

Real-Time Simulation and Testing: Hardware-in-the-Loop

Hardware-in-the-Loop (HIL) Simulation and Testing with Simulink Real-Time^TM and Speedgoat target computers.

Continental: Accelerated Development Using Rapid Control Prototyping

This project shows a solution whereby engineers can quickly move from SIL to HIL using a Speedgoat system with programmable FPGA technology instead of an original ECU. 

CPU, FPGA, and I/O Solutions for Real-Time Simulation and Testing with Simulink

In this webinar, MathWorks together with Speedgoat will showcase how to perform real-time simulation and testing, enabling you to rapidly and continuously test and prove your designs, from desktop simulation to testing your designs in real time on hardware platforms.

Model-Based Design for Predictive Maintenance, Code Generation and Real-Time Testing

This video shows how to automatically generate C code from classification models. First, you’ll see how to validate your algorithm on the desktop. Then, once it is validated, the video will show how to generate code. Next, the video walks through how to use Simulink® to deploy the classification model onto a B&R PLC, and then test it on a real-time representation of the system using a Speedgoat machine.

Motion Planning and Experimental Validation for an Autonomous Bicycle

This paper introduces a prototype autonomous two-wheeled vehicle developed for experimental verification of motion planning and control algorithms. Finally, it presents and discusses experiments run on the actual vehicle for a particular maneuver. It emphasizes the differences between the trajectories created by different vehicle models.

Publication on ieeexplore.ieee.org

A Software Architecture for an Autonomous Racecar

The authors present a detailed description of the software architecture used in the autonomous Roborace vehicles by the TUM-Team. The architecture combines the autonomous software functions perception, planning, and control, which are modularized for use on different hardware and to drive the car on high-speed racetracks. 

Publication on ieeexplore.ieee.org

Hardware-in-the-Loop (HIL) Testing of Battery Management System (BMS) using Simulink Real-Time and Speedgoat target hardware

This webinar demonstrates how engineers can perform hardware-in-the-loop (HIL) testing to validate and test their Battery Management Systems design using Simulink Real-Time and Speedgoat Target hardware.

It showcases the modeling of a battery pack and battery management algorithms such as SOC estimation and cell balancing using Simulink. The webinar also shows how to perform HIL simulation by running the battery pack plant model in real time on Speedgoat test system, to find errors before deploying the actual hardware in the field

A Real-Time Simulation Environment for Autonomous Vehicles in Highly Dynamic Driving Scenarios

In May 2018, a group of researchers from the Technical University of Munich (TUM) won the first Roborace Human + Machine Challenge. TUM's autonomous driving software stack manages environment perception, autonomous navigation, and trajectory tracking.