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Friday, 20 April 2012 |
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MSc presentation:
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State of health estimation of a Li-ion battery based on subspace identification
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Speaker:
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David Beijer
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Supervisor:
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Prof.dr.ir. M. Verhaegen, dr. M. Corno
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Location:
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Zaal F, Faculty 3mE
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Time:
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13:30 until 14:15
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Abstract:
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This research has looked into the problem of State-of-Health (SOH) estimation of li-ion batteries for Electric Vehicle (EV) applications. The goal is to track some features of the battery which can be linked to the SOH. These features are sought in the dynamic behaviour between the current and the voltage of the battery. The hypothesis was that the dynamics of these kind of batteries could be modeled accurately by means of (a variation of) a Hammerstein Wiener model, In that case the parameters of these models can be used for comparison against a library of known models which would result in an estimate of the SOH of the battery. The models of the batteries were obtained by using numerical black-box modeling techniques based on subspace identification.This research used a PBSID algorithm, augmented with weighted basis functions to represent the static nonlinearities at the input and output. This algorithm was then applied to data obtained from running identification experiments on batteries which were brought to different SOH.
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