AI Summary & Key Takeaways
AI InsightThese profiles were integrated into MATLAB/Simulink-based vehicle dynamics and powertrain simulations to realistically estimate traction force, road resistance, regenerative braking potential, and overall energy demand.
📌 3 Key Takeaways
Abstract
In this study, a route-specific driving cycle for the Beylikdüzü–Söğütlüçeşme–Beylikdüzü Istanbul Metrobus line was developed to reflect its operational and topographical characteristics. The cycle considers real-world gradients, frequent stops, and high passenger loads, addressing the limitations of standard flat-road assumptions. High-resolution telemetry data were collected from 132 LF25 diesel buses, including speed, acceleration, stop times, and segment-based speed profiles. Five representative vehicles were selected based on statistical consistency, and vehicle motion was divided into acceleration, constant speed, deceleration, and stop phases. Time-based speed and distance values were calculated for each segment, and stop altitudes along the route were obtained from Google Earth with linear interpolation applied to generate continuous distance–altitude profiles. These profiles were integrated into MATLAB/Simulink-based vehicle dynamics and powertrain simulations to realistically estimate traction force, road resistance, regenerative braking potential, and overall energy demand. The simulation framework enables evaluation of energy consumption and powertrain performance for 25-meter bi-articulated electric Metrobus vehicles. The developed driving cycle provides a robust representation of real operational conditions and serves as a foundation for future studies on energy efficiency, motor torque requirements, and battery performance. Furthermore, the methodology can be adapted for electric or fuel-cell public transit vehicles, supporting the transition toward zero-emission urban transportation in Istanbul.