Team Details

As of 2022, this class has been integrated into the other two classes.

TUW Racing

University Technische Universität Wien
AT Wien TU short 122
LocationWien, Austria
Homepagehttps://www.tuwienracing.at/
Social Media facebook X
CV Team TUW Racing
EV Team TU Wien Racing
Short Linktid.fsg.one/788

Event Profile

Past Events

Car 441 – 2017
2017
Car #441
Info
Back in October, Alumni and some of the members of the 2016 electric team decided to attempt the upgrade of EDGE8 to an autonomous vehicle. Since the team remained strong in the 2016/17 season and accumulated high interest from students, university and companies, we soon began redesigning the vehicle, and continued to maintain and test it alongside the new electric car. We welcomed the challenge to combine the design of the vehicle with new developments in control engineering and robotics.
Engineering Design Priorities:
robustness self-development lightweight design testability efficiency observability
Car Specifications
General
Frame Construction one piece CFRP Monocoque
Material sandwich structure with aluminum honeycomb and rohacell core
Overall Length (mm) 2845
Overall Width (mm) 1395
Overall Height (mm) 1118
Wheelbase (mm) 1575
Track Front (mm) 1200
Track Rear (mm) 1160
Weight Front (kg) 73
Weight Rear (kg) 91
Suspension Double unequal length A-Arm, pull rod actuated horizontally oriented spring and damper
Tyres 6.0/18.0-10
Wheels 7.0x10, 25mm offset, one piece CFRP rim
Drive Type 1 spur & 1 planetary stage, at upright
Differential n/a
Cooling radiator with electric fan, electric water pump
Brake System 4-Disk system, self designed brake disks, adjustable brake balance, AP calipers F/R
Electronics self-developed LTE telemetry with custom HTTP telemetry server and client
Powertrain
Number of Motors 2
Motor Location Rear Right, Rear Left
Max Motor Power 2x40kW
Motor Type TUWR-E3, self developed
Max Motor RPM 16.000
Motor Controller Infineon Hybrid Kit
Max System Voltage (V) 265V
Electrode Materials LiPo
Accumulator Capacity 4,66 kWh
Transmission Ratio Primary 1:11,9
Transmission Ratio Secondary n/a
Driverless System
Processing Units Nvidia Jetson TX2
Processing Units FLOPS 1500
Processing Units Power (W) 30
Cameras 1x ZED Stereo Camera
Radar Sensors -
LiDAR Sensors 1x Hokuyo 30LX
Other Sensors 1x Correvit
DV System Highlights Motion-aware perception systems for significant reduction of required processing power in the vision system; landmark-based SLAM

FS past achievements due to World Ranking Data Base

Date Event Teams Rank BP CM ED DV SP DV AC AX EN EF Pe Total Engine
2017.08
15
7.
13.
6.
8.
-
-
-
-
-
-10.00
299.19
x 1