simulink student challenge -凯发k8网页登录

1st place

controlling the torque vectoring of an electric race car - simulink challenge 2016

julian ulrich - karlsruhe institute of technology

this project targets controlling the torque vectoring of four wheels independently for an electric race car. with this torque vectoring mechanism, more torque is distributed to the outer wheels and less lateral forces at the front axils. this leads to a higher lateral acceleration during curve racing. ka-raceing successfully implemented model-based design with matlab and simulink. this technology, along with the collaboration of mechanical engineers and computer scientists, helped the racing team to achieve first place in the electric overall category of formula student germany (fsg) 2016.

2nd place

avionics flight demonstrator (avd march 2016)

philippe françois - cranfield university

the avionics flight demonstrator project develops a platform for integrating and testing the design of major avionics components onboard an aircraft. this video demonstrates integration of flight management system, 6-dof flight control system, landing system, and the guidance display system. the project uses simulink to simulate automatic flight guidance and trajectory tracking, automatic landing, and real time flight parameter visualization. simulink also seamlessly communicates between multiple computers (each performing its own operations) using udp protocol. this video demonstrates how complex systems can be designed in a modular fashion using the model-based design approach in simulink.

3rd place

thermographic camera - #simulinkchallenge2016

viktor panasiuk - kiev polytechnic institute

the thermographic camera project demonstrates how image processing techniques can be used to create an augmented reality that shows the variation of temperature in a room. multiple temperature sensors are placed around a room and their data is read through the serial port. each sensor is accompanied by a small led light, which is configured to blink in a sequence in order to identify the sensor’s position in the video frame. the temperature and location data is then used to create a temperature profile of the room. the temperature profile is visualized using a color map and then superimposed on the original video. the end result is an impressive display of the temperature variations across the room.