# An Efficient GPS Algorithm for Maximizing Electric Vehicle Range
## 1 Introduction  
In recent years, there has been a large growth in new electric vehicle models across various segments, from sedans to trucks, reflecting the mainstream acceptance of electric vehicles [1]. The future of electric vehicles appears promising, with advancements in affordability, range, and reliability expected to drive further adoption [2]. Governments worldwide are also incentivizing the transition to electric vehicles, further fueling their popularity [3]. With the continued decline in battery costs and improvements in charging infrastructure, electric vehicles are poised to eventually replace gasoline-powered vehicles, according to some experts [4]. Additionally, electric vehicles are becoming more economical to use as maintenance costs are significantly lower compared to fuel-based vehicles, and recharging costs are often a quarter of refueling costs in some countries [5].  
Based on current EV growth and lessons from prior technological revolutions, researchers at RMI suggest a curve model which predicts that EV sales will expand at least four-fold by 2030, accounting for 62 percent to 86 percent of worldwide automobile sales [6]. EV sales may surpass internal combustion engine (ICE) sales as soon as 2026, as shown in Figure 1[6]. The graph depicts the projected market share of electric vehicles (EVs) and internal combustion engine (ICE) vehicles over the years from 2015 to 2030. The red line until year 2022 represents the \"EV-actuals\", which shows the historical market share of EVs, starting at a low percentage in 2015 and gradually increasing over time. The red line after year 2022 labeled \"EV-faster\" shows a forecasted faster adoption of EVs, reaching a higher market share by 2030 [7].  
The green line until year 2022 represents the \"ICE-actuals\", which shows the historical market share of ICE vehicles, starting at a high percentage in 2015 and steadily declining over time [6]. The green line after year 2022 labeled \"ICE-faster\" shows a forecasted faster decline in ICE vehicle market share [7]. The lighter green line labeled \"ICE-fast\" and the yellow line labeled \"EV-fast\" provide alternative forecasts, with ICE vehicles declining more rapidly and EVs gaining market share more quickly by 2030 [7].  
However, there are still challenges regarding the range per charge and charging time of electric vehicles [8]. For instance, while using a fuel-based vehicle, refueling is quick and gasoline stations are widely available; therefore, the total trip time is mainly composed of road time, with refueling time being negligible [9]. In contrast, electric vehicles may require 3-6 h for charging, depending on the availability of charging points infrastructure and the remaining energy capacity in the battery of the vehicle, which significantly impacts the total trip time [8]. Figure 2 shows a full comparison between the total time spent on a journey using an EV vs. ICE, and shows the time spent in refueling/recharging.  
Moreover, the proposed algorithm has many advantages over some other algorithms such as considering all vehicle parameters when calculating the energy consumed. Additionally, wind speed and direction are taken into consideration. This requires few data as input to select the optimum route with minimal energy consumed. This energy con  
Figure 1: Global EV and ICE market share forecasting as (%).  
Figure 2: EV and ICE journey time plus refueling/recharging time comparison.  
servation translates into monetary savings for the journey and ultimately extends the battery's lifespan.