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AUTHOR(S):

Rakshitha Ravi, Usha Surendra

 

TITLE

Charge and Health Status Estimation of a Lithium Ion Battery in an Electric Vehicle Using Cell Balancing IOT Modelling Techniques

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ABSTRACT

In Present scenario Internal Combustion Engines [ICE] is overcome by Electric Vehicles [EV] due to advantages like reduction in carbon-di-oxide [CO2] emission, cost. Advancement in electric vehicles are extensively going on and one such concept is Battery management system [BMS]in Battery Electric vehicle. In Battery Electric Vehicle there are many types of batteries and from the literature survey Lithium Ion Battery can be concluded to be suitable as it is advantageous in weight, cost, energy density and many aspects. Battery may be overcharged or it may undergo faults. Hence a reliable management system is required to control the Electric vehicle [EV]. In this paper two battery charge estimation models namely, open circuit voltage and Kalman filter has been considered. From the simulation results obtained it is found that data retrieval is difficult in open circuit voltage method can be achieved using Kalman filter and found out to be satisfactory.

KEYWORDS

Battery management system, Open Circuit Voltage, Kalman filter, State of Charge.

 

Cite this paper

Rakshitha Ravi, Usha Surendra. (2021) Charge and Health Status Estimation of a Lithium Ion Battery in an Electric Vehicle Using Cell Balancing IOT Modelling Techniques. International Journal of Chemistry and Chemical Engineering Systems, 6, 52-60

 

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