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@article{154548,
        author = {Swathi Ramesh R  and Dr.M. S. Shashikala},
        title = {Study of Various methods on the estimation of State of Charge and State of Health for lithium ion batteries in electric vehicles },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {11},
        pages = {489-475},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=154548},
        abstract = {With electric vehicles (EVs) being extensively accepted as a clean technology to break carbon emigrations in ultramodern transportation, lithium-ion batteries (LIBs) have surfaced as the dominant energy storehouse medium in EVs due to their superior parcels, like high energy density, long lifetime, and low tone- discharge. Performing real- time condition monitoring of LIBs, especially directly estimating the state of charge (SOC) and state of health (SOH), is pivotal to keep the LIBs work under safe state and maximize their performance. Still, due to thenon-linear dynamics caused by the electrochemical characteristics in LIBs, the accurate estimations of SOC and SOH are still gruelling and numerous technologies have been developed to break this challenge. This paper reviews and discusses the state-of-the- art online SOC and SOH evaluation technologies published within the recent five times in view of their advantages and limitations. As SOC and SOH are explosively identified, the common estimation styles are specifically reviewed and bandied. Grounded on the disquisition, this study ultimately summarizes the crucial issues and suggests unborn work in the real- time battery operation technology. It's believed that this review will give precious support for unborn academic exploration and marketable operations.

},
        keywords = {State-of-charge, state-of-health, lithium-ion battery, fractional-order model, dual Kalman filter.},
        month = {},
        }