English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper presents the analysis, design, and experimental validation of parameter identification of battery/supercapacitor (SC) hybrid energy storage system (HESS) for the purpose of condition monitoring and maximum power estimation. The analytic bounds on the error of battery and SC parameter identification, considering voltage measurement noise, are obtained based on the Fisher information matrix and Cramer–Rao bound analysis. The identification of different parameters requires different signal patterns to ensure high accuracy, rendering tradeoffs in the multiparameter identification process. With an appropriately designed current profile, HESS parameters are identified using recursive least squares with a forgetting factor. The identified parameters are then used to estimate the maximum power capability of the HESS. The maximum power capabilities of the battery and SC are estimated for both 1 and 30 s time horizons. The parameter identification algorithm can be applied to systems including either batteries or SCs when the optimal excitation current can be injected. Experimental validation is conducted on an HESS test-bed, which shows that the proposed algorithm is effective in estimating the HESS maximum power based on appropriate current excitation.

Parameter Identification and Maximum Power Estimation of Battery/Supercapacitor Hybrid Energy Storage System Based on Cramer–Rao Bound Analysis