# An Efficient GPS Algorithm for Maximizing Electric Vehicle Range
## 4 Results
### Simulation Case Studies
#### 4.1.3 Case 3: Impact of Elevation on kwh Consumption  
In this case, a comparative analysis of two routes leading to the same destination with identical vehicle models is used. This investigation aims to facilitate the selection of the most optimal and cost-effective route, considering variations in topology and elevation along different paths. The chosen location for assessment lies along the road to Hurghada, Egypt, as illustrated in Figure 10. Google Maps suggests a route that offers a 4-min time advantage over the alternative route, with comprehensive data provided in Table 4. In this case, the main factor that will cause a very large difference in consumption is the difference in topologies as shown in Figure 11[46].  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Rout** & **Rout 1** & **Rout 2** \\ \hline Distance & 102 km & 80.2 km \\ \hline Time & 1 h, 4 min & 1 h, 8 min \\ \hline Maximum Inclination & 710 m above sea level & 86 m above sea level \\ \hline Average inclination & 263.8 m & 31.3 m \\ \hline \hline \end{tabular}
\end{table}
Table 4: Data of two suggested routes by Google Maps.  
Figure 9: SOC (%) difference for three scenarios in Case 2 at different wind speeds and directions.  
From Table 4, it became apparent that the suggested route is less than the other by 4 min. However, a deeper analysis of energy consumption between the two routes reveals pertinent insights, given that Route 1 has a speed limit of 120 km/h [47], while Route 2 imposes a lower limit of 80 km/h [48]. Moreover, in this evaluation, the influence of wind is disregarded, as its effect remains consistent across both routes according to the Windy Mobile app [49]. The accompanying graph depicts the vehicle's speed profile for Route 1 over time until it reaches its destination, as shown in Figure 12a.  
Figure 11: Different topologies of routes in Case 3 [46].  
Figure 10: The routes suggested by Google Maps with distance and time.  
Figure 12b provides insight into the state of charge (SOC) upon arrival at the destination. From the graph, the data shown provide that the energy consumed by the vehicle is about 48% from the battery as the SOC is 52%. This means that the remaining battery capacity level following this trip is 23.4 kwh.  
For Route 2, Figure 13a shows the velocity vs. time. Although it took more time to reach the destination, but in terms of energy consumed if Route 2 was chosen the energy consumed is about 28% of the battery capacity, which can be considered as 12.6 kwh as shown in Figure 13b.  
When comparing both routes, if Route 1 was chosen, then 4 min will be saved from the traveling time. But if Route 2 was chosen as shown in Figure 10, this will save about 46% of the energy consumed in Route 1 or it can be described as 10.8 kwh saved from the battery capacity. Moreover, if the total duration of the journey was calculated for both routes, the result will show that the time saved can be up to 1 h and a half from the total journey time if Route 2 was chosen as shown in Table 5.  
Figure 12: (a) Route 1 Driving Cycle for ID3 Volkswagen. (b) SOC% for the energy consumed in Route 1.  
Also, if the time for charging is calculated using a 40 kW DC charger, this can alter the charging time to 35 min for Route 1 and 19 min for Route 2. This means that the ratio between both routes is double the time needed when selecting Route 1 as your first option.