Real Time Passenger Mass Estimation for e-scooters

Dockless electric scooters have proven, nowadays, to be a competitive solution in the urban micro-mobility environment. However, recent studies underline how electric scooters’ sustainability is closely related to their lifetime and recharging frequency. Since these depend significantly on the onboard mass, this paper presents two approaches, i.e., gray-box and black-box, to estimate this parameter relying only on the measurements from GPS and IMU sensors installed on the e-scooter. The robustness and the accuracy of the mass estimation is tested on extensive datasets collected in ad-hoc experimental campaigns.