Statistical Analysis and Electric Range Distributions in Battery EVs and Hybrid EVs

In this work, a study on different energy sources for battery charging of EVs is carried out. The EV_Population_Data is collected and analyzed for the dependency of people on EVs and the different types of EVs. Solar power, photovoltaic power and other renewable energy sources are explored for charging possibility in EVs as well as house hold applications. To predict the battery requirements in current and future situations, the analysis is done based on number EVs manufactured by different companies, their year of manufacture and model of the EV so that the company responsibility for the near future to supply the required number of batteries can be estimated. Python coding in anaconda jupyter notebook is used for statistical analysis of different types of EVs and their population dependency city-wise in a country.

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Publication Details

Published
2024-12-22
DOI
https://doi.org/10.1109/cicn63059.2024.10847548
Citations
1
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.20
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Statistical Analysis and Electric Range Distributions in Battery EVs and Hybrid EVs

Meenugu Venkateshwarlu, S. Radha, S. Siva Priyanka, P. Nagabushanam et al.
1 citations
Advanced Battery Technologies Research
0.20
article

Statistical Analysis and Electric Range Distributions in Battery EVs and Hybrid EVs

Meenugu Venkateshwarlu, S. Radha, S. Siva Priyanka, P. Nagabushanam, K. Vasanth, Prakash Kumar Jala
article en
1 citations

Abstract

In this work, a study on different energy sources for battery charging of EVs is carried out. The EV_Population_Data is collected and analyzed for the dependency of people on EVs and the different types of EVs. Solar power, photovoltaic power and other renewable energy sources are explored for charging possibility in EVs as well as house hold applications. To predict the battery requirements in current and future situations, the analysis is done based on number EVs manufactured by different companies, their year of manufacture and model of the EV so that the company responsibility for the near future to supply the required number of batteries can be estimated. Python coding in anaconda jupyter notebook is used for statistical analysis of different types of EVs and their population dependency city-wise in a country.

Karunya University (IN), Chaitanya Bharathi Institute of Technology (IN), Institute of Engineering (NP)
Affordable and clean energy
Openalex Percentile: Top 46%
Advanced Battery Technologies Research
0.20
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Statistical Analysis and Electric Range Distributions in Battery EVs and Hybrid EVs — Meenugu Venkateshwarlu, S. Radha, et al. · (2024) | TGRS Research Map | TGRS