Data logging is a key element when testing and validating technologies for autonomous driving. But how can you make sure your data logging processes are efficient and reliable? Our colleague Patrik Morávek answers questions like this in his blog article "My 8 Tips for Efficient Data Logging".
Do you need to emulate the electrical interface between an electric vehicle and the charging station for your testing activities? This is where our new DS5367 Smart Charging Plug Simulator comes into play. The extension for the dSPACE Smart Charging Solution offers numerous manipulation options and supports all common charging communication standards.
Video: Optimizing Controller Code for Electric Drives
For the controller software of electric drives, performance is often critical. During the prototyping phase, you can use high-performance prototyping systems and FPGAs. In production vehicles, however, the lower costs and ready availability of lower-performance, embedded microcontrollers can give you a competitive edge.Join our free webinar for tips on how to optimize a controller model to achieve the target values imposed by your production hardware.
Video: Boost Your Simulink / TargetLink Modeling Efficiency
Working on large and complex Simulink and TargetLink models doesn’t have to be a tedious and time-consuming task. In this video podcast episode, Ferry Bachmann from Model Engineering Solutions (MES) and Carsten Rustemeier from dSPACE show how you can complete modeling tasks faster, safer, and with less frustration.
Did you know that dSPACE offers a cooling unit for our compact and robust in-vehicle prototyping system, the MicroAutoBox III?
This means you can also use the MicroAutoBox in field tests where all processors are constantly working under full load. Active cooling extends the permissible temperature range so that the MicroAutoBox III also functions safely under harsh conditions.
The cooling unit can be easily integrated without changing the footprint of the MicroAutoBox III.
An optimal data-driven development solution consists of a fully integrated pipeline for the continuous development of the machine-learning-based functions needed for autonomous driving. dSPACE ensures that you successfully master your data pipeline challenges with the right technologies, methods, and outstanding expertise.