Modelling approach for assessing influential factors for EV energy performance

In a context of rising vehicles' electrification, understanding powertrain performance in different operation conditions remains a difficult task. This work develops an electric vehicle model to study influential parameters such as battery capacity, battery energy density, driving environment (speed and temperature) and driving behaviour (aggressiveness). The developed model, implemented in MATLAB-Simulink, includes 5 sub-systems (vehicle model, motor, battery, regenerative braking and speed profile) and evaluates in 1 Hz drive-cycles state of charge, average energy consumption per km and range. The model estimates energy consumption and range of electric vehicles with an error less than 2% for seven electric vehicles in Worldwide Harmonized Light Vehicles Test Procedure drive-cycles. The study demonstrated that increasing battery energy capacity by three-fold, range can be increased by 294%, with an increase of vehicle mass by 1.5 kg/Wh. While the change in energy density of the battery from 157 Wh/kg to 224 Wh/kg shows a reduction of 2-4% in energy consumption. Besides, maintaining average speed between 25 and 40 km per hour results in maximum range, whereas aggressive driving has a negative influence and reduces vehicle range. Also, the same vehicle can result in a range difference of 25-35% in northern and southern European countries due to varying atmospheric conditions.