# A Framework for Communicating and Building a Digital Twin Model of the Electric Car
## 4 Discussion
The track is modeled based on satellite data, taking into account changes in terrain height. The first step is to make a sketch of the track contour based on satellite photos from a top view, as in Figure 4. Points are added at altitudes corresponding to the altitude [m.a.s.l.] of the corresponding track points based on Google Earth satellite data. In order for the car to move along the desired track, the points of contact between the vehicle and the ground must be determined. For this purpose, the 3D Contact function is used. Four contacts are assigned (each corresponding to each of the vehicle's wheels) with the same physical values. * Creating a simulation in the Siemens NX Motion Simulation module, taking into account the forces acting on the car in the real environment. Atmospheric conditions were modeled. According to the diagram from the Weather Underground website, the wind blows from west to east at a speed of 2 [mph], which after conversion gives a value of 0.89408 [m/s] (Figure 8). * Reflection of the car's passage in a virtual environment based on data from the telemetry application. Data obtained from the telemetry system allow for plotting the actual trajectory of the car (Figure 9a). After running a simulation that mirrored part of the Dunsfold track, the car goes around the corner on the same trajectory as the real car in the race. Once this result is achieved, the model is considered tuned and ready for testing (Figure 9b)
* Optimization of the car's driving path in the selected corner. The next stage is to route the digital twin along a new route. The goal is to obtain higher travel speeds at a  
Figure 8: Wind parameters. Figure 9: (a) Car motion trajectory based on data from the telemetry system; (b) simulation of the car trajectory on the Dunsfold track. simi-lar current level, i.e., approximately 20A. The test run and the comparison of the movement trajectories are presented in Figure 10. The green line shows the theoretical trajectory, while the blue line reflects the trajectory obtained from the GPS position of the telemetry module. After analysis of the track, differences were noticed between the driving resulting from the vehicle's trajectory and the theoretically determined track optimized due to the criterion of minimizing the centrifugal force. For the Chicago Corner curve, the length of the track resulting from telemetry was 76,000 mm, and the track after optimization was 82,000 mm. The speed of the car while turning at Chicago Corner was also compared. The entry speed was 55 km/h for measurements from the telemetry module and the twin at Chicago Corner. The speed at the exit of the corner was 54 km/h in the case of the telemetry and 57.8 km/h in the case of the twin. The average current was 27A when driving through Chicago Corner in the case of measurements from the telemetry module. The average current was 23A in the case of the twin moving along the optimized trajectory. After carrying out the simulation process, it was shown that it is possible to negotiate the bend more economically and at a higher speed. The electric car moving along the designated trajectory showed a greater increase in speed after passing the turn. This translates directly into lower energy losses when traversing the analyzed track. Optimization is necessary to negotiate the same turn on different driving lines, one real and the other theoretically determined, and with the same drive parameters and after taking into account the forces acting on the car. To understand best practices for turning more economically and at higher speeds, it is important to analyze the relationship between historical and real-time data about the car and the environment.