Enhanced State and Parameter Estimation within Reconfigurable Battery Systems for Electric Vehicles

Schneider, Dominik; Liebhart, Bernhard; Endisch, Christian; Kennel, Ralph

doi:10.1109/cpeee54404.2022.9738700

Cited by 1 publication

(2 citation statements)

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“…On the contrary, the switching operation was more beneficial for v 1 and R 1 using the WLTP. In summary, it still can be said that switching had a greater influence on the estimation with the highway profile than with the WLTP, which is consistent with previous results [25]. But this trend was different for the state and parameter estimation.…”

Section: Resultssupporting

confidence: 89%

“…Hence, switching might increase the cell temperature and lead to a higher aging degradation rate. To reduce the current RMS, switching strategies can be applied to limit switching to periods with low currents or low excitation in a frequency domain, e.g., using the Goertzel algorithm [13,25]. Furthermore, in the work of Ngaleu et al [27], the influence of switching at 50 Hz and 10 kHz on aging was investigated using the same cell type as in this paper.…”

Section: Resultsmentioning

confidence: 99%

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Experimental Investigation of State and Parameter Estimation within Reconfigurable Battery Systems

2023

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The battery system is one of the most-important, but also -critical components in the electric power-train. The battery’s system states and parameters are commonly tracked by the battery monitoring system. However, in reality, the accuracy of the state and parameter estimation may suffer from insufficient excitation of the system. Since the current states and parameters serve as the basis for many battery management system functions, this might lead to incorrect operation and severe damage. Reconfigurable battery systems allow enhancing the system’s excitation by applying a switching operation. In this contribution, the state and parameter estimation of a reconfigurable battery module were simulated and tested experimentally. Thereby, a low-exciting and a high-exciting drive cycle were compared. Furthermore, the switching patterns were applied to enhance the excitation and, hence, improve the estimation of an extended Kalman filter. The cells were switched via a pulse-width modulation signal, and the influence of frequency and duty cycle variation on the estimation accuracy were investigated. Compared to the low-excitation input, a significant improvement in the estimation of up to 46% for the state of charge and 78% for the internal resistance were achieved. Hereby, low frequencies and duty cycles proved to be particularly advantageous. Switching, however, has only a limited influence on an already highly excited system and may lead to additional aging due to higher heat generation.

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Section: Resultssupporting

confidence: 89%