High-Fidelity Drive Cycle Based Battery Discharge Modeling for Electric Scooters Using GPS Derived Torque Dynamics

Abstract

A high-fidelity simulation framework has been developed to model the battery discharge behavior of electric scooters by integrating experimental measurements with dynamic system parameters such as torque and GPS derived velocity. To support the construction of highly representative drive cycles, a purpose built, high-resolution data logging system was employed to capture real- time electrical parameters including current and voltage at a 1 Hz sampling frequency. This high-resolution dataset enabled the generation of fine-grained, fidelity enhanced representations of real-world operational profiles, thereby reinforcing the empirical foundation of the simulation framework. The model facilitates Net Present Value (NPV)-based cost evaluations by incorporating battery aging and capacity degradation. Validated against two real-world drive cycles, the simulation achieved Root Mean Square Error (RMSE) values ranging from 1% to 2% when compared to experimental current data. The results demonstrate the model's robustness in capturing transient dynamics and long-term degradation effects, offering a reliable foundation for techno-economic analysis and aging-aware battery management in electric mobility applications.