An Investigation on the Effects of Input Parameters on the Dynamic and Electric Consumption of Electric Motorcycles

The purpose of this paper is to study how input parameters affect the dynamic characteristics and electric consumption characteristics of an electric motorcycle. To achieve this goal, a simulation model of the electric motorcycle, including dynamic models and battery models were established based on mathematical models and using the MATLAB SIMULINK software (Parnas Tower 14th Floor521 Teheran-street Gangnam-district Seoul 06164 Korea). The simulation model was used to determine the velocity, propulsion torque, electric consumption characteristics with variable electric motorcycle mass, driver mass, wheel radius, frontal area, and transmission ratio. Through the simulation study, the paper found that when the electric motorcycle mass was increased from 60 kg to 100 kg, the maximum velocity decreased by 5.45%, the moving distance was reduced by 5.89%, and electric consumption increased by 0.11%. Following increased driver mass from 48 kg to 88 kg, the velocity and moving distance decreased by 5.45% and 5.89%, respectively, while also increasing electric consumption by 0.11%. When the wheel radius was changed from 0.205 m to 0.245 m, the maximum velocity increased by 11%, the moving distance increased by 11.2%, and electric consumption increased by 0.11%. When the frontal area was increased from 0.52 m2 to 0.92 m2, the velocity and moving distance decreased by 2.43% and 2.06%, respectively, while electric consumption increased by 0.04%. When the transmission ratio was increased from 2.66 to 4.94, the velocity and moving distance increased from 30.74 km/h to 70.7 km/h and from 303.12 m to 710.44 m, respectively, while electric consumption increased by 0.16%. Finally, an experimental study is conducted to examine the dynamics of the electric motorcycle. The experimental results have the same trend with simulation in the same initial condition. Through combination simulation and experiment, the researcher can optimize the dynamic and electric consumption of an electric motorcycle