Novel methode of state-of-charge estimation using in-situ impedance measurement: Single cells in-situ impedance measurement based state-of-charge estimation for LiFePO4 — Li2TO3 Battery Cells with a real BMS

Rathmann, Hannes; Weber, Christoph; Benecke, W.; Eichholz, J.; Kaehler, Dirk

doi:10.1109/iecon.2014.7048806

Cited by 7 publications

(2 citation statements)

References 8 publications

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“…[13][14][15] However, these techniques have significant disadvantages as stated in the Liu et al 16 study. Looking at the literature studies for the LTO battery, it is seen that incremental capacity analysis, extended Kalman filter (EKF), [17][18][19] nonlinear autoregressive with exogenous inputs, 20 electrochemical impedance spectroscopy, 21 and model reference adaptive system 22 techniques are used in SoC estimation. When these studies in the literature are examined, it is seen that the most successful method is EKF.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear estimator‐based state of charge estimation for lithium titanate oxide battery in energy storage systems

Muratoglu

Alkaya

2023

Energy Storage

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Fuel savings, energy savings, and reduction of CO2 emissions are the key requirements in electric and hybrid electric vehicles (EVs and HEVs). These requirements are achieved through the usage of start‐stop systems, high‐rate energy boost during acceleration, and recovery of the energy during braking. Unfortunately, the commonly used lithium‐ion batteries are not a sufficient solution, although their performance is enhanced by supercapacitors. This hybrid system used is only a temporary solution. Therefore, lithium‐titanate‐oxide batteries (Li4Ti5O12—LTO), show high‐rate discharging and charging performance, high power capability, excellent cycle life, and improved cycle stability at wide‐rate temperatures and current rates are promising candidates for HEV and EV applications. There is a need to monitor the state of charge (SoC) for the reliability, performance, and safety of LTO batteries with the help of a battery management system. However, the conventional SoC estimation methods, such as open circuit voltage, Coulomb counting, artificial neural networks, fuzzy logic, and linear Kalman filter algorithm become insufficient. In this paper, a new nonlinear approach for the SoC estimation of an LTO battery is presented. The approach combines the static battery model and the sigma point Kalman filter (SPKF) algorithm while adapting to both constant load and dynamic load. The results show that the SPKF algorithm successfully estimated the SoC of the LTO battery under various initial SoC initialization values. It is also supported by various metric errors calculated.

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Section: Introductionmentioning

confidence: 99%

Nonlinear estimator‐based state of charge estimation for lithium titanate oxide battery in energy storage systems

Muratoglu

Alkaya

2023

Energy Storage

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“…Another major challenge in the application of battery models is the identification of model parameters. In this field, the Levenberg-Marquardt (L-M) algorithm [21,22] and intelligent optimization algorithms such as the particle swarm optimization (PSO) algorithm [23,24] are commonly used. The intelligent optimization algorithm has strong universality and good applicability to the model structure and can overcome the problem of the L-M algorithm easily falling into local optima.…”

Section: Introductionmentioning

confidence: 99%

Online Broadband Impedance Identification for Lithium-Ion Batteries Based on a Nonlinear Equivalent Circuit Model

Pan

Wang

Zhang

et al. 2023

WEVJ

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Models play a crucial role in explaining internal processes, estimating states, and managing lithium-ion batteries. Electrochemical models can effectively illustrate the battery’s mechanism; however, their complexity renders them unsuitable for onboard use in electric vehicles. On the other hand, equivalent circuit models (ECMs) utilize a simple set of circuit elements to simulate voltage–current characteristics. This approach is less complex and easier to implement. However, most ECMs do not currently account for the nonlinear impact of operating conditions on battery impedance, making it difficult to obtain accurate wideband impedance characteristics of the battery when used in online applications. This article delves into the intrinsic mechanism of batteries and discusses the influence of nonstationary conditions on impedance. An ECM designed for non-steady state conditions is presented. Online adaptive adjustment of model parameters is achieved using the forgetting factor recursive least squares (FFRLS) algorithm and varied parameters approach (VPA) algorithm. Experimental results demonstrate the impressive performance of the model and parameter identification method, enabling the accurate acquisition of online impedance.

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In-Situ EV Battery Electrochemical Impedance Spectroscopy with Pack-Level Current Perturbation from a 400V-to-12V Triple-Active-Bridge

Assadi

Gong

Wang

et al. 2022

2022 IEEE Applied Power Electronics Conference and Exposition (APEC)

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Novel methode of state-of-charge estimation using in-situ impedance measurement: Single cells in-situ impedance measurement based state-of-charge estimation for LiFePO₄ — Li₂TO₃ Battery Cells with a real BMS

Cited by 7 publications

References 8 publications

Nonlinear estimator‐based state of charge estimation for lithium titanate oxide battery in energy storage systems

Nonlinear estimator‐based state of charge estimation for lithium titanate oxide battery in energy storage systems

Online Broadband Impedance Identification for Lithium-Ion Batteries Based on a Nonlinear Equivalent Circuit Model

In-Situ EV Battery Electrochemical Impedance Spectroscopy with Pack-Level Current Perturbation from a 400V-to-12V Triple-Active-Bridge

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