Abstract
Next generation of transportation in the form of electric vehicles relies on better operation and control of large battery packs. The individual modules in large battery packs generally do not have identical characteristics and may degrade differently due to manufacturing variability and other factors. Degraded battery modules waste more power, affecting the performance and economy for the whole battery pack. Also, such impact varies with different trip patterns. It will be cost effective if we evaluate the performance of the battery modules prior to replacing the complete battery pack. The knowledge of the driving cycle and battery internal resistance will help to make decision to replace the worst battery modules and directly cutdown on user expenditure to replace the battery.Also, optimizing the performance of battery during the driving trip is the challenging task to achieve. The knowledge of energy prices of the grid, internal resistance of the lithium-ion battery pack on the electric vehicle, the age of the battery and distance travelled by the electric vehicle are very important factors on which the cost of daily driving cycle is dependent. In near future, the energy consumed by the electric vehicles will create a major consumer market for the smart grids. The smart grid system is complemented by the renewable energy sources that contribute and support the grid. The electric vehicles are not only predicted as energy consumers but also as dynamic sources of energy. These vehicles can now travel more than 100 miles with a single charging cycle whereas average day to day commute is well below the maximum capacity of these vehicles. The improvement of the electric grid to the next generation infrastructure i.e. ‘Smart Grid’ will enable diverse opportunities to contribute the energy and balance the load on the grid. The information about the grid like price quality, load etc. will be available to the people very easily. This information can be useful to make the energy grid more economical and environment friendly. We have used the information for price of energy on the grid to optimize the cost of daily driving cycle. The goal of this project is to accurately predict the battery behavior for the daily driving cycle. The prediction of battery behavior will help the driver to decide the optimum charging patterns, energy consumed during driving and the surplus energy available in the batteries. The prior knowledge of the battery behavior, price of the energy on the grid and the trip travel will help the driver to minimize the cost of travel on daily basis as well as throughout the life of the battery.
Citations
IRE Journals:
Mohd Asif , Akash Kumar Singh , Chetan S. More
"Fast Charging Of Electric Vehicle Using Matlab Simulation" Iconic Research And Engineering Journals Volume 6 Issue 1 2022 Page 112-119
IEEE:
Mohd Asif , Akash Kumar Singh , Chetan S. More
"Fast Charging Of Electric Vehicle Using Matlab Simulation" Iconic Research And Engineering Journals, 6(1)
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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