UKF Based Estimation of SOC and Core Temperature of a Lithium Ion Cell Using an Electrical Cell Model

Mitra, Desham; Mukhopadhyay, Siddhartha

doi:10.1109/indicon45594.2018.8987074

Cited by 5 publications

(1 citation statement)

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“…Instead, the unscented transformation is combined with a Kalman Filter algorithm, and a suitable sampling strategy is applied to approximate the state variables, which is able to avoid the error induced by the EKF hair due to its disregard for higher-order terms [18]. However, the UKF algorithm needs to recalculate the sigma point set at the end of each cycle, which will lead to a large computational effort for the whole algorithm and high requirements for the central processing chip of real-time SOC estimation [19][20]. Therefore, this paper uses a Simplified-sphere Unscented Kalman Filter (SUKF) algorithm to implement SOC estimation, which simplifies the hypersphere monomorphic sampling strategy, thus reducing the computational effort of the whole algorithm.…”

Section: Journal Of Informatics Electrical and Electronicsmentioning

confidence: 99%

SOC Estimation for Electrical Vehicle lithium Batteries base on Simplified-spherical Un-scented Kalman Filtering

Wang¹

2022

J. Infor. Electr. Electron. Eng.

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In order to develop electric vehicles, it is vital to be able to accurately estimate the state charge (SOC) of a lithium battery. To address the problem that the Extended Kalman Filter (EKF) algorithm leads to the Taylor expansion truncation of the higher-order system. In this paper, a system of state-space equations is established based on the second-order equivalent circuit model, and a simplified-sphere sample approach is used to improve the Unscented Kalman Filter (UKF) algorithm. The SOC estimation performance of the three algorithms is tested under constant current discharge, pulse discharge conditions, and UDC conditions, respectively. The simulation results show that Simplified-spherical Unscented Kalman Filtering (SUKF) has smaller errors between SOC estimation and theoretical reference values than EKF and UKF. The SUKF is less computationally intensive than UKF and has better timeliness in the onboard battery management system.

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Section: Journal Of Informatics Electrical and Electronicsmentioning

confidence: 99%