State of health estimation based on improved double-extended Kalman filter

Chao Wang, Daniel Ioan Stroe, Jingsong Qiu, Shunli Wang, Wenhua Xu, Xiaoxia Li, Yang Li

Publikation: Bidrag til bog/antologi/rapport/konference proceedingBidrag til bog/antologiForskningpeer review

Abstract

In this chapter, the state of health (SOH) of aviation lithium-ion batteries is estimated from the perspective of ohmic internal resistance and capacity. The dual time scale Adaptive double extended kalman filter (ADEKF) algorithm based on extended Kalman filter is studied, and adaptive noise correction is introduced to solve the estimation error problem caused by variable system noise. State of charge (SOC) and SOH are estimated from two-time scales to avoid the impact of the fluctuation of SOC estimation on the capacity, resulting in a smaller time scale. Obtain ohmic internal resistance through RLS online parameter identification, and then obtain SOH value. Considering the advantages and disadvantages of ohmic resistance and capacitance estimation, a two-factor SOH estimation method is proposed. This method combines ohmic resistance and capacitance estimation to obtain the optimal solution for the health state.

OriginalsprogEngelsk
TitelState Estimation Strategies in Lithium-ion Battery Management Systems
RedaktørerShunli Wang, Kailong Liu, Yujie Wang, Daniel-Ioan Stroe, Carlos Fernandez, Josep M. Guerrero
Antal sider20
ForlagElsevier
Publikationsdato2023
Sider313-332
Kapitel15
ISBN (Trykt)9780443161612
ISBN (Elektronisk)9780443161605
DOI
StatusUdgivet - 2023

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© 2023 Elsevier Inc. All rights reserved.

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