Acceleration | 0-100km/h: 2,0s |
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Power Output | 4x28kW |
Weight | 226kg |
PWd3.19
Monocoque | CFRP one-piece |
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Aerodynamics | Side and rear wing, skid plate and splitter |
Motor | 4 wheel hub motors |
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Top performance | per Motor: 28 kW |
Gearbox | 1 ½ stage planetary gear |
Battery container | Central battery container with 7.5 kWh |
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Cells | Samsung INR 18650 25 R |
Maximum voltage | 580V |
Control unit | ETAS |
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Driving dynamics control systems | Torque vectoring, recuperation, traction control, power limitation |
Telemetry | Live Telemetry via 2.4 GHz WLAN |
Dashboard | Self-developed dashboard |
Wheelbase | 1540mm |
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Front track width | 1150mm |
Rear track width | 1128mm |
Tires | 7,5″x10″ Hoosier Slicks |
Rims | 10″ CFRP rims with aluminum star |
A-Arm | Double A-Arm |
Dampers | Pushrod actuated damper |
Cameras | 2x Intel D435, 1x Bosch SVC2 |
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Sensors | Kistler Correvit SFII, Bosch MM5.10-R acceleration sensor, VectorNav VN-300 INS |
Processing Units | 2x NVIDIA Jetson TX2, ETAS ES910 |
Environment recognition | Object recognition via a neural network |
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Mapping / Localization | In-house developed C ++ libraries with a focus on storage space optimization |
Test environment | Hardware in the loop test bench |
Toolchain | C++, Python, Matlab, IPG Carmaker |
Trajectory planning | Model-based off-policy reinforcement learning to optimize lap times |
Training automation | In-house developed software for data set management, automatic hyperparameter optimization and management of machines in the training cluster |