Fractional extended and unscented Kalman filtering for state of charge estimation of lithium-ion batteries
2018 Annual American Control Conference (ACC), 2018•ieeexplore.ieee.org
Two state of charge estimation methods using fractional order extended and unscented
Kalman filter and a nonlinear variable fractional order battery model are implemented. Both,
battery model and Kalman filters are evaluated and compared using measurements of an
actual lithium-ion polymer battery cell. The observability of the battery model and the
influence of an initialization function on the estimation algorithms is investigated.
Kalman filter and a nonlinear variable fractional order battery model are implemented. Both,
battery model and Kalman filters are evaluated and compared using measurements of an
actual lithium-ion polymer battery cell. The observability of the battery model and the
influence of an initialization function on the estimation algorithms is investigated.
Two state of charge estimation methods using fractional order extended and unscented Kalman filter and a nonlinear variable fractional order battery model are implemented. Both, battery model and Kalman filters are evaluated and compared using measurements of an actual lithium-ion polymer battery cell. The observability of the battery model and the influence of an initialization function on the estimation algorithms is investigated.
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