Upon introducing these features to velocity models resulted in significant improvement in their predictive performance. This finding further emphasizes the importance of considering trips-specific road conditions and individual variations when modeling EV battery SOC. Moreover, velocity-based models offer a practical and scalable alternative for real-world SOC estimation, given they are widely available. The intuitive nature of velocity data is more easily understood by drivers than current-based data, which facilitates the provision of real-time feedback to optimize the charge consumption. However, to ensure accurate predictions, it is essential to account for human influenced variations in each trip during modeling. This paper also explores the accuracy of predictive models on early trip data.