# An Efficient GPS Algorithm for Maximizing Electric Vehicle Range
## 4 Results
### Simulation Case Studies
#### 4.1.2 Case 2: Impact of Wind Speed on kwh Consumption  
In this case, a comparison will be carried out to study the effect of wind speed and direction on the same vehicle and same road. Three scenarios will be executed to figure out the effect of wind, the first one involves the vehicle navigating the road under calm wind conditions, with a wind speed of 0 m/s. Subsequently, the second scenario replicates the same vehicle and road conditions but introduces a headwind of 10 m/s, opposing the vehicle's direction of motion. Finally, the third scenario features a wind speed of 10 m/s aligned with the vehicle's direction of travel.  
As shown below, the accompanying figure illustrates the vehicle's driving cycle, characterized by a constant speed of 25 m/s (approximately 90 km/h) which is maintained for a duration of 2040 s (34 min), resulting in the coverage of 51 km as shown in Figure 8. It is important to note that these results are derived under a fixed road inclination of 0 degrees, a parameter consistent across all scenarios. This graph will be the same in each of the three following scenarios, so that the only changed variable in Case 2 is the wind speed and its direction.  
As for the first scenario, Figure 9 illustrates that the green line represents the energy consumption or state of charge (SOC%) achieved by the vehicle after covering 51 km at a constant speed. It reveals that the SOC presently stands at 75%, indicating that 25% of the battery's energy has been depleted. Given that the vehicle model used is the Volkswagen ID3 Pure model, equipped with a battery capacity of 45 kWh, this means that the energy consumption amounts to approximately 11.25 kWh.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Vehicle Type** & **SOC\%** & **DOD\%** & **Energy Consumption** \\ \hline Tesla Model S Plaid & 76.5\% & 23.5\% & 23.5 kWh \\ \hline BMW i3 & 18\% & 82\% & 18 kWh \\ \hline Nissan e-NV200 & 0\% & 100\% & Did not reach \\ \hline Rivian R1T & 69\% & 31\% & 41.85 kWh \\ \hline Volkswagen ID3 & 50\% & 50\% & 22.5 kWh \\ \hline GMC Hummer & 78.5\% & 21.5\% & 45.15 kWh \\ \hline Volkswagen E-Lavida & 38\% & 62\% & 18.6 kWh \\ \hline \end{tabular}
\end{table}
Table 3: SOC% and DOD% of different vehicles used in Scenario 2 at 120 km/h fixed speed.  
Figure 8: Driving Cycle used in Case 2.  
Also, from the same figure, the blue line pertains to Scenario 2, featuring the same vehicle model, fixed speed, and distance covered. However, in this instance, the wind speed registers at 10 m/s, opposing the vehicle's motion. Notably, the state of charge (SOC) of the vehicle stands at 65%, signifying a 10% increase in energy consumption compared to Scenario 1, totaling 15.75 kWh consumed, with 4.5 kWh extra energy consumed only due to wind speed and direction. This incremental loss underscores the pivotal role of wind direction, a crucial consideration when selecting the optimum route for electric vehicles.  
As for the red line in Figure 9, the positive effect of wind speed on the energy consumption is shown as the SOC when the wind direction aligned with the vehicle motion reached 82%, which means that the wind reduced the energy consumed by about 7% when comparing it to Scenario 1. Therefore, the energy consumed in this scenario is 8.1 kwh. A comparison between Scenarios 2 and 3 reveals that about 7.65 kwh was saved from the battery, which is about 48.5% from the energy consumed in Scenario 1.