E ects of driving style on energy usage in battery electric vehicles

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Examensarbete för masterexamen
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2020
Författare
Berglund, Emma
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Environmental problems such as emissions and greenhouse gases have put pressure on the automotive industry. There is a growing interest in energy e cient electric vehicles and model-based approach is a powerful tool to design new electric vehicles. This thesis employs system-level simulations to investigate the e ects of driving aggressiveness on energy usage in battery electric vehicles. A Lithium-Ion battery pack is designed in GT-AutoLion and integrated into the existing electric vehicle model in GT-SUITE. Five di erent drive cycles; HWY, UDDS, LA92, NEDC and WLTC were used to represent highway, urban, city driving and their combination. The driving aggressiveness is modeled by separately modifying velocity and acceleration. This by scaling the time and speed traces with following scaling factors; 0.8, 0.9, 1.0, 1.1 and 1.2. All simulations are carried out using GT-SUITE. The result shows the e ects of driving aggressiveness and how it can be analyzed based on the sensitivity of energy consumption to di erent driving styles. The energy consumption sensitivity trends are explained in relation to energy losses and energy recovered by regenerative braking. The main ndings of this work are that the relation between the energy consumption sensitivity for the drive cycles are linear. HWY has the highest energy consumption sensitivity and UDDS the lowest when modifying the velocity. When modifying the acceleration UDDS has the highest energy consumption sensitivity and HWY has the lowest. It is shown that driving aggressiveness has a great impact on the energy consumption and its sensitivity. The main conclusion is that simulations can predict the energy consumption considered given drive cycles and driving aggressiveness.
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Lithion Ion battery , Energy Consumption , Battery Electric Vehicle model , Drive cycle , Driving aggressiveness , Electric Vehicle simulation , GT-SUITE , GT-AutoLion
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