Performance simulation and predictive model for a multi-mode parallel hybrid electric scooter drive

Abstract

SUMMARYThis paper presents a parallel hybrid electric scooter model developed on MATLAB-Simulink. The hybrid electric scooter model was developed to further understand and analyze as well as to predict its performance before proper construction of the prototype begins. The model consists of four main models that formed the complete hybrid scooter model: battery model, engine model, DC motor model and the dynamics model. The multi-mode controller predicts the required parameters to operate the scooter in an optimize condition. Experimental data were gathered and thus compared to the simulated data to check the model's feasibility and accuracy on four distinct driving cycles: modified urban dynamometer driving schedule (UDDS), New York city cycle (NYCC), European driving cycle (ECE-15) and modified highway fuel economy driving schedule (HWFET). Basic studies showed that the model developed had a maximum of 4% error. Maximum error achieved between the theoretical and the experimental readings is about 3.15%, which is for the modified HWFET cycle. Other cycles have acceptable errors; UDDS cycle with 1.91%, NYCC cycle with a low 0.68% and ECE-15 cycle with 1.15%. Operating costs between the internal combustion engine mode, motor mode and hybrid mode were also estimated, where final results showed an 18% reduction of the overall fuel consumption using the multi-mode controller between hybrid scooters and conventional scooters. The fuel consumptions were also predicted and compared the estimated results with one commercially available hybrid scooter, Piaggio Vespa MP3 hybrid scooter. Primary results showed a 4.4% increase in distance travelled per kilometer.

Optimal Design of Electric Micromobility Vehicles

“…Narrowing the scope towards previous research on the design of e-scooters and e-mopeds, we identify the following contributions: Whilst simulation-based approaches reveal the capabilities of (hybrid) electric two-wheelers [15]- [17], efforts have been made to optimize the design of the electric motor of scooters and mopeds using finite-element modeling [18], [19] combined with gradient-based [20] or evolutionary algorithms [21]. However, these methods do not jointly optimize the design and control of the full powertrain from a system-level perspective, potentially leading to suboptimal solutions [22].…”