Identification of a bilinear and parameter-varying model for lithium-ion batteries by subspace methods

In this paper, subspace methods are used to identify a dynamic model for high-power lithium-ion cells for hybrid vehicles which is valid within the whole operating range. The lithium-ion battery cells regarded in this contribution have non-linear dynamic behavior which basically depends on battery cell temperature. Therefore, bilinear and parameter-varying model parts are necessary, which can be summarized within one linear-parameter varying (LPV) model. In combination with subspace methods, the presented modeling approach allows a global identification of the model. In contrast to many publications, the identification of the model is based on measurements where common dynamic current-voltage profiles from normal vehicle operation were applied to battery cells. Although the resulting system model has only low complexity, it is still able to describe the battery cell behavior within the entire temperature operation range due to the chosen LPV structure.

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