The issues pertaining to global warming and greenhouse effects have become more prominent. One of the measures being taken by the world countries to address these key issues is adoption of Electrical Vehicle (EV) technology that has revolutionized the mobility industry by gradually grabbing the market share of fossil fuel-based automobiles. A battery-operated electric vehicle (BEV) uses chemical energy stored in a rechargeable battery pack for operation, and emits zero pollutants. Apart from plug-in charging, the BEVs charge their batteries through a regenerative braking system by recovering kinetic energy lost during braking. The EV manufacturers put forth relentless effort to enhance the performance of EVs through new technologies. The efficiency of regenerative braking, and battery capacity largely affect certain performance parameter, i.e., factors of EVs. An analysis of key performance parameters and their relations are of great importance as far as the performance enhancement is concerned. Industries do employ simulation software for carrying out these analyses, but without considering interrelation between performance-influencing factors. An analysis of correlating factors that influence the EV performance can be of good tool to help group the factors that can affect one another. In this paper, an attempt is made to conduct a correlation study between performance-influencing factors of various commercially available electric vehicles. The factors considered for this study are; battery capacity, power, driving range and pick-up. The relations between these factors are established through conducting Pearson correlation. This study will help guide the EV manufacturers to understand the parametric relations to optimize the performance of their EVs. In addition, the findings obtained from the post-sale analysis of the performance factors can be useful in validating the simulation results.


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    Titel :

    Parametric performance analysis of battery operated electric vehicle


    Beteiligte:
    Loganathan, M. K. (Autor:in) / Tan, C. M. (Autor:in) / Sultana, Sahnin (Autor:in) / Hsieh, I-Yun Lisa (Autor:in) / Kumaraswamidhas, L. A. (Autor:in) / Rai, R. N. (Autor:in)


    Erscheinungsdatum :

    21.01.2021


    Format / Umfang :

    340937 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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