Jaroslav Jirkovský (Humusoft s.r.o.)
A virtual vehicle is a term used to virtualize a vehicle's development cycle, relying on simulations of vehicle behaviour at the system level. Virtual vehicle simulations allow you to quickly gain insight into vehicle behaviour in the real world, perform virtual testing of different scenarios and verify the functionality of embedded software (embedded sw). The use of a virtual vehicle helps to accelerate variant assessment, safely study boundary cases and improve the overall quality of the system being developed. Typical steps in the creation of a virtual vehicle include vehicle modelling, embedded software integration, definition of test scenarios, simulations and results analysis.
In the field of electromobility, simulation models can be used to design and optimize systems typical of electric vehicles. These may include battery modeling and development of BMS (battery management system), fuel cell modeling, modeling traction drives and their control units, integration and testing of control algorithms, or the use of data-oriented approaches and artificial intelligence.
Jiří Minarik, Petr Liškář (Eaton elektrotechnika s.r.o.)
A demonstration of a virtual EV model configurable with one or more different motors, inverters and transmissions at the same time, which users can customize according to their wishes or use only partial parts of it for their work. The presentation is followed by a demonstration of one of the possible approaches to simulate driving a two-wheeler in a virtual or real environment using GPS data, including driving dynamics influences and the work of advanced stabilization systems.
Michal Blaho (Humusoft s.r.o.)
The development of robotic and autonomous systems belongs to modern areas of research. Researchers and engineers of such systems try to design and tune algorithms that meet the most stringent requirements in areas such as motion planning or environmental perception for mobile robots, UAVs or manipulators. The Robot Operating System (ROS) is also a frequent part of the solutions, which helps in acquiring and analyzing data from the sensors. In this lecture, we will talk about interesting MATLAB tools for the development of robotic and autonomous systems.
Tomáš Fridrich (Humusoft s.r.o.)
The automotive industry has focused on the development of autonomous driving in recent years. Deployment of ADAS systems in production vehicles precedes long years of development and testing. The functionality and reliability of the sensors need to be subjected to rigorous testing. Millions of kilometres travelled and thousands of hours of recording under development, guarding our road safety. The lecture will tell you more about data collection, generating your own traffic scenarios and testing sensors for ADAS systems.