Team Details

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

Elbflorace Driverless

University Technische Universität Dresden
DE Dresden TU short 83
LocationDresden, Germany
Homepagehttps://elbflorace.de/
Social Media
CV Team Elbflorace
EV Team ELBFLORACE e.V.
Short Linktid.fsg.one/838

Past Events

Car 411 – 2018
2018
Car #411
Info
11x
This is the first season for Elbflorace Driverless. Because of that, we wanted to keep everything simple in order to have a solid basis for coming years. Our main focus is therefore on reliability and sustainability regarding a) the vehicles autonomous system, e.g. path planning and mapping and b) on the vehicles electric system.
Engineering Design Priorities:
Reliability Safety Simplicity
Car Specifications
General
Frame Construction full size CFRP Monocoque
Material Pre-impregnated CFRP with Aluminium honeycomb as core material
Overall L 2955 mm
Overall W 1407 mm
Overall H 1146 mm
Wheelbase 1550 mm
Track (Fr) 1200 mm
Track (Rr) 1150 mm
Weight with 68kg driver (Fr) 110 kg
Weight with 68kg driver (Rr) 110 kg
Suspension Double unequal length A-Arm, Pushrod
Tyres (Fr / Rr) Continental
Wheels (Fr / Rr) 7x13, 30mm offset, Mg rim
Drive Type 1 stage planetary gear integrated to upr
Cooling two seperated cooling circles for motors and inverters, Radiators mounted at side
Brake System 4-Disk system, self developed rotors and self developed front brake caliper
Electronics selfdesigned Live-Telemetry System via WLAN, Kalman filter for determining velocity
Powertrain
Number of Motors 2
Motor Location Rear
Max Motor Power (per motor) 35kW kW
Motor Type AMK
Max Motor RPM (highest) 15500 rpm
Motor Controller AMK Inverter
Max System Voltage 600 V
Electrode Materials LiCoO2
Combined Accumulator Capacity 7 kWh
Transmission Ratio (Primary) 1:35.32 : 1
Driverless System
Processing unit(s) Teensy 3.2, MicroAutoBox with Embedded PC
Floating Point Operations Per Second of all processing units that are working for the DV system 345.60 GigaFLOPS
Power consumption of all processing units that are working for the DV system 48 W
Lidar sensor(s) Velodyne Puck HiRes
Highlights of the DV system Optimized version of Euclidean Clustering, 3d-Cone Detection using Machine
Learning, recursive path planning using Delaunay Triangulation

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
2025.08
42
7.
-
-
6.
6.
-
11.
5.
-
0.00
370.08
2025.08
24
10.
-
-
8.
-
-
-
-
-
0.00
249.90
2024.08
27
4.
-
-
10.
1.
1.
1.
8.
-
0.00
365.00
2024.08
13
4.
8.
6.
5.
3.
-
2.
2.
-
-25.00
765.75
2023.08
30
20.
-
-
18.
-
-
-
-
-
0.00
90.00
2023.08
22
3.
2.
9.
15.
2.
6.
5.
2.
2.
-20.00
729.28
2022.09
10
4.
3.
5.
4.
2.
3.
3.
-
-
0.00
440.10
2022.08
19
14.
-
-
9.
-
-
-
-
-
0.00
105.00
2021.08
12
6.
5.
3.
4.
-
-
-
-
-
0.00
421.20
2019.07
14
13.
13.
12.
13.
-
-
-
-
-
0.00
249.20
2018.08
17
13.
2.
11.
14.
-
-
-
-
-
-15.00
213.00
2018.07
6
4.
4.
4.
4.
-
-
-
-
-
-110.00
163.14
x 12