Developing and Testing Power Electronic Components in Electric Vehicles
Learn how our cutting-edge solutions streamline the validation process for DC/DC converters and other power electronic components used in electric vehicles. Get an overview of typical use cases and the various solutions we offer for them.
Radar Test Bench for Component Tests, Simple ADAS Function Tests, and ECU Validation
The new Radar Test Bench – Essential 2D makes it possible to perform azimuth and elevation simulation for a single target. The test bench is highly flexible because it can be used with a standard Windows PC or with a SCALEXIO real-time system and allows for manual or motorized ECU positioning.
RTMaps: Trusted middleware for real-time multisensor applications
Up to 60% of development effort for ADAS/AD software is spent on middleware optimization. RTMaps saves you this overhead. Accelerate your software development with RTMaps and jump-start your innovations.
This video shows you how to prepare software-in-the-loop (SIL) testing with virtual ECUs (V-ECUs) for Adaptive AUTOSAR applications.
Accelerate your developments for ADAS/AD by using SIL testing in early validations without the real ECU hardware and when running multiple simulations in parallel.
A true-to-life depiction of reality within a simulation, a digital twin, can be used to carry out high-precision virtual test drives. In contrast to gaming applications, in which the human eye can be fooled, the vehicle development process always requires physically correct computations. The new dSPACE solution for sensor-realistic simulation offers next-generation visualization and realistic sensors (camera, radar, lidar), thus making it possible to test and validate driving functions in real time or even faster.
Parallel execution of complex and CPU-intensive simulation models
The SCALEXIO portfolio has been updated to include a new SCALEXIO Processing Unit featuring a 16-core Intel Xeon Gold Processor. This makes it possible for engineers to use high-fidelity, physically realistic models, increases model accuracy, and makes HIL simulations more realistic.
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 this question and others in this video.