The rise of hybrid and electric vehicles involves some new technological challenges, especially when it comes to batteries. In these applications batteries will be loaded very dynamically and they have to perform under different conditions. In this research an electrical model of a lithium-ion battery is presented, which allows to predict the voltage response of the battery. The developed model consists of a voltage source, some resistors and some capacitors. The values of these components are influenced by temperature, current rate and State-of-Charge. To estimate the parameters under different conditions two parameter estimation techniques are implemented in Matlab/Simulink: the Parameter Estimation Tool and an Extended Kaiman filter. Afterwards, the parameter values under different conditions are stored in look-up tables. A simulation model makes it possible to validate the results of the proposed model using different current profiles. The model error is defined as the difference between the measured and the simulated voltage. With both techniques a RMS value of the percent error was achieved with a maximum of 3.6 %. On the one hand the result can be improved by defining a more accurate algorithm to determine the Stateof- Charge. On the other hand the parameter estimation process can be refined by optimizing the used load cycles.


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    Title :

    Characterization of a battery model using parameter estimation techniques


    Contributors:


    Publication date :

    2012


    Size :

    11 Seiten, 12 Bilder, 3 Tabellen, 14 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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