Sai
Shashank Mukkera
SURF Analyzing the Impacts of Temperature on Electric Vehicle Adoption Rates Across Multiple US States Mathematical/Computation Sciences
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Authors:
Sai Shashank Mukkera
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About Paper:
Despite the advancements in electric vehicle (EV) technology, less than 10% of vehicles in the US are EVs, indicating that the country remains an early adopter of this technology. Although EVs offer numerous advantages, their penetration remains low, particularly in regions with extreme temperatures. While numerous studies have examined the impacts of policy and sociodemographic factors on EV adoption, the influence of temperature has not been thoroughly explored. This study examines the influence of temperature on the adoption of EVs across various climatic regions in the United States. Our previous research focused on California and New York revealed that temperature is among the most important predictor of battery electric vehicle (BEV) and plug-in hybrid electric vehicle (PHEV) population change rate and penetration. Building on these findings, we extend our analysis to five additional states, such as North Carolina and Minnesota, to capture a broader range of climate variations. We gather detailed ZIP code-level data on land surface and air temperatures, sociodemographic characteristics, charging infrastructure availability, and land use patterns. Utilizing logistic curves, we build a parametric model to understand the impacts of temperature on the rate of EV adoption. Our work is the first to analyze how temperature influences the parameters of the logistic curve, providing insights into the rate of adoption in different climatic regions. We expect our results to reaffirm that temperature is a critical predictor of BEV and PHEV adoption rates. Through these advancements, we aim to provide a more detailed understanding of the factors influencing EV adoption and support the development of targeted strategies for promoting sustainable transportation across diverse climatic regions in the United States. Keywords: Electric Vehicles; Machine Learning; Temperature Variation; Sustainable Transportation; Climate Impact
Source:
Purdue University / 2024
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Co-authors:
Sai Shashank Mukkera