Abstract

Internal combustion engine (ICE) vehicles have a longer driving range with a full tank of gas than lithium-ion battery-powered electric vehicles (EVs). Alongside having a higher purchase cost and a lack of charging infrastructure, the range of EVs is a large deterrent to potential buyers. One solution to increasing the range of EVs is using a battery pack with a higher capacity. However, increasing the capacity typically involves an increase in lithium-ion battery cells, which leads to a higher weight, higher vehicle cost, lower energy efficiency, and higher battery charging time. In addition, regenerative braking recovers the vehicle's kinetic energy which is related to speed and weight. To find the optimal battery pack size, a numeric road test simulation can be used to determine how battery pack size affects energy efficiency, driving range, charging time, and cost. This is more optimal than a real-life road test since inconsistent variables like traffic conditions and weather can be controlled. This paper applies work-energy mathematic modeling of an electric vehicle under different EPA dynamometer driving schedules to investigate the problem proposed above, using an EV model with 21700 type lithium-ion cells. In addition, total vehicle weight, motor efficiency, wheel sizes/weight, and the weight of passengers will also be considered. The simulation revealed that when the total vehicle weight reaches a certain point, it can regenerate significant kinetic energy back to the battery pack to increase the range. Figure 1

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