<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The focus of this paper is to develop reliable observer and filtering techniques for finite-dimensional battery models that adequately describe the charging and discharging behaviors. For this purpose, an experimentally validated battery model taken from the literature is extended by a mathematical description that represents parameter variations caused by aging. </p><p>The corresponding disturbance models account for the fact that neither the state of charge, nor the above-mentioned parameter variations are directly accessible by measurements. Moreover, this work provides a comparison of the performance of different observer and filtering techniques as well as a development of estimation procedures that guarantee a reliable detection of large parameter variations. For that reason, different charging and discharging current profiles of batteries are investigated by numerical simulations. The estimation procedures considered in this paper are, firstly, a nonlinear Luenberger-type state observer with an offline calculated gain scheduling approach, secondly, a continuous-time extended Kalman filter and, thirdly, a hybrid extended Kalman filter, where the corresponding filter gains are computed online.</p></abstract>

The focus of this paper is to develop reliable observer and filtering techniques for finite-dimensional battery models that adequately describe the charging and discharging behaviors. For this purpose, an experimentally validated battery model taken from the literature is extended by a mathematical description that represents parameter variations caused by aging. The corresponding disturbance models account for the fact that neither the state of charge, nor the above-mentioned parameter variations are directly accessible by measurements. Moreover, this work provides a comparison of the performance of different observer and filtering techniques as well as a development of estimation procedures that guarantee a reliable detection of large parameter variations. For that reason, different charging and discharging current profiles of batteries are investigated by numerical simulations. The estimation procedures considered in this paper are, firstly, a nonlinear Luenberger-type state observer with an offline calculated gain scheduling approach, secondly, a continuous-time extended Kalman filter and, thirdly, a hybrid extended Kalman filter, where the corresponding filter gains are computed online.

Nonlinear state observers and extended Kalman filters for battery systems

Chair of Mechatronics University of Rostock, Justus-von-Liebig-Weg 6, D-18059 Rostock, Germany

International Journal of Applied Mathematics and Computer Science

{"article-title":"Nonlinear state observers and extended Kalman filters for battery systems"}

The focus of this paper is to develop reliable observer and filtering techniques for finite-dimensional battery models that adequately describe the charging...

Nonlinear state observers and extended Kalman filters for battery systems

Data publikacji: 30 wrz 2013

Zakres stron: 539 - 556

DOI: https://doi.org/10.2478/amcs-2013-0041

This content is open access.