The electrification of transportation is revolutionizing the automotive and logistics sectors, with electric vehicles (EVs) assuming an increasingly pivotal role in both passenger mobility and commercial activities. As the adoption of EVs rises, the necessity for precise range estimation becomes essential, especially under diverse operational circumstances, including vehicle and battery characteristics, driving conditions, environmental influences, vehicle configurations, and user-specific behaviors. Among the varying factors, a key fluctuating one is user behavior—most notably, increased payload, which significantly affects EV range. A key business challenge lies in the significant variability of EV range due to changes in vehicle load, which can affect performance, operational efficiency, and cost-effectiveness—especially for fleet-based services. This research aims to tackle the technical deficiency in forecasting electric vehicle (EV) range under various payload conditions. Conventional range estimation techniques frequently overlook real-world factors such as extra cargo weight, resulting in inefficient route planning, heightened energy usage, and unexpected charging needs
Payload-induced range degradation can lead to a considerable deviation from the estimated range, adversely affecting logistics efficiency and raising the total cost of ownership. The aim of this study is to create a robust, simulation-based framework to assess EV range in both standard and elevated payload scenarios, thus improving prediction accuracy and guiding data-driven operational decisions. Vehicle comprehensive simulation tool was used to model under various load conditions for EV performance. The key parameters like road gradient, driving cycles, vehicle payload, regenerative braking, battery dynamics, motor efficiency, motor torque and speed are incorporated in model. The two main sceneries considered for simulation like nominal load/payload which reflect typical usage and incremental payload which is indicative for last mile delivery. The results demonstrated that a higher payload leads to typical reduction in driving range, with more pronounced impacts noted in urban driving sceneries because of frequent acceleration and deceleration.