Predicting how far an
Electric Vehicle (EV) can travel on a single charge is challenging due to variables like weather, traffic, battery health, and payload. These factors make it difficult for drivers to estimate charging needs accurately, which remains a significant concern for potential EV adopters, particularly those new to the technology.
Unlike internal combustion engine (ICE) vehicles, calculating EV range is far more complex. Many automakers overestimate remaining range by as much as 20%. For instance, if your EV predicts a remaining range of 160km, the actual distance might only be around 120km. This discrepancy arises because traditional range calculations rely heavily on internal sensors, often neglecting external factors like temperature and road elevation, which can significantly impact battery performance.
Tests conducted by HERE reveal stark differences in range under varying conditions. For example, an EV with an 88 kWh battery could cover 550km during an urban commute with a single occupant, minimal speed, and no use of heating or air conditioning. However, the same vehicle traveling at higher speeds with three occupants, luggage, and the heating system engaged sees its range drop to 380km—a 31% decrease.
Enhancing Accuracy with Advanced Tools
HERE addresses these challenges using advanced mapping and data integration techniques. By combining real-time data such as traffic conditions,
Battery type, and vehicle specifications, HERE creates more accurate predictions of remaining range.
Effective route planning tools are crucial for EV drivers, especially given the longer charging times compared to ICE vehicles. Depending on the charger type, recharging can take anywhere from 45 minutes to over four hours. Machine learning plays a role in optimizing this process by predicting charger availability and reliability, dynamically updating the driver’s route based on real-time conditions.
Chris Handley, VP of Dynamic & Spatial Content at HERE, highlights the fragmented nature of current EV Charging infrastructure. Issues like varying plug types, payment systems, and faulty charge points have led to failures in one out of five charging attempts in the US. Accurate predictions about charger functionality and availability are critical for reducing these frustrations.
Future Developments in EV Technology
As EV support technology evolves, more factors will be incorporated into range predictions. Historical data will enhance weather and traffic forecasts, while personalized insights—such as driver behavior and typical vehicle loads—will further refine accuracy. While these advancements won’t directly increase the number of charging stations, they will help drivers plan their journeys with greater confidence and convenience.
By integrating these tools, HERE aims to reduce range anxiety and support the broader adoption of EVs, ensuring drivers have the information they need to travel with peace of mind.
