Enhancing Range Prediction Accuracy for the BEV: Bridging the Gap Between Simulation and Real-World Testing

Accurate range estimation in battery electric vehicles (BEVs) is essential for optimizing performance, energy efficiency, and customer expectations. This study investigates the discrepancies between physical test data and simulation predictions for the Jeep Wagoneer model. A detailed range delta analysis identifies key contributors to the observed deviations, including regenerative braking inefficiencies, increased propulsion demand, auxiliary loads, and estimated drivetrain losses within the Electric Drive Module (EDM) during traction and regen. Results indicate that the test vehicle exhibits lower regenerative braking efficiency and higher traction and lower regen consumption than predicted by simulations, primarily due to EDM inefficiencies and friction brake usage during regeneration. The study underscores the importance of refining simulation methodologies by integrating real-world, test based EDM loss maps to improve accuracy and better align predictive models with actual vehicle performance. Future work will focus on enhancing simulation fidelity and minimizing range estimation deviations to support BEV development and validation.