Data-Driven State of Health Estimation of Li-Ion Batteries With RPT-Reduced Experimental Data

Kim, Jungsoo; Chun, Huiyong; Kim, Minho; Yu, Jungwook; Kim, Kwangrae; Kim, Taegyun; Han, Soohee

doi:10.1109/access.2019.2932719

Cited by 41 publications

(17 citation statements)

References 19 publications

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“…Table I lists the electrochemical, geometric, kinetic and transport properties of a Lithium Cobalt Oxide (LCO) cell which we used in our simulations. For the P2D model, we used v2.0 of the LIONSIMBA toolbox [35] which has been widely applied for such benchmarking purposes in battery modeling literature [32], [36]- [39]. Table II lists the conditions pertaining to numerical simulation of the models discussed in this work.…”

Section: B Simulation-based Analysis Of Quadratic Approximation Modelmentioning

confidence: 99%

A Composite Single Particle Lithium-Ion Battery Model Through System Identification

Gopalakrishnan

Offer

2022

IEEE Trans. Contr. Syst. Technol.

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In the realm of Lithium-ion (Li-ion) battery modeling, owing to its simplicity, the Single Particle Model (SPM) has long been considered to be a promising Reduced Order Model (ROM) candidate to usher in the era of Physics-Inspired Models (PIMs) in embedded applications. However, at high load currents, the standard SPM exhibits poor accuracies in computing the cell's terminal voltage, thereby rendering it unsuitable as the plant model in state-estimation tasks. A comprehensive evaluation of the salient electrolyte-enhanced SPMs from literature reveals that current solutions are either mathematically intractable or overly simplistic. For the ionic concentration in the electrolyte, the well-known quadratic approximation model, which straddles the boundary of computational complexity and mathematical tractability, reveals a poor temporal performance, particularly at the current collector interfaces. In this work, we retain the spatial dynamics of the quadratic approximation model, whilst proposing a novel approach using system identification techniques for its temporal dynamics. By employing linear approximations for the relevant subsystems, we identify discrete-time transfer functions of the de-biased number of moles per unit area of lithium ions in the electrolyte within each electrode region, yielding improved spatiotemporal accuracies for the electrolyte concentration profile. We then augment the standard SPM with the new system identificationbased electrolyte dynamics to arrive at an Electrolyte-Enhanced Composite Single Particle Model (EECSPM). Finally, we demonstrate superior performance of the EECSPM when compared with the incumbent state-of-the-art, thereby representing a concrete advancement towards the goal of using PIMs in real-time applications.

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Section: B Simulation-based Analysis Of Quadratic Approximation Modelmentioning

confidence: 99%

A Composite Single Particle Lithium-Ion Battery Model Through System Identification

Gopalakrishnan

Offer

2022

IEEE Trans. Contr. Syst. Technol.

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“…As expected, more people per household is equivalent to more vehicles per house- Prefer not to answer This survey showed that the public is becoming sensitive to environmental issues. For instance, in a multiple-choice question on the main advantages of an electric vehicle, the most voted answer (23) was the environmental advantage (see Figure 12). The second most selected answer was the low operating cost that an EV has.…”

Section: Ev Adoption Obstacles-uve and Deco Surveysmentioning

confidence: 99%

Mining Electric Vehicle Adoption of Users

Rodrigues

Albuquerque

Ferreira

et al. 2021

WEVJ

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The increase of greenhouse gas emissions into the atmosphere, and their adverse effects on the environment, have prompted the search for alternative energy sources to fossil fuels. One of the solutions gaining ground is the electrification of various human activities, such as the transport sector. This trend has fueled a growing need for electrical energy storage in lithium batteries. Precisely knowing the degree of degradation that this type of battery accumulates over its useful life is necessary to bring economic benefits, both for companies and citizens. This paper aims to answer the current need by proposing two research questions about electric motor vehicles. The first focuses on habits EV owners practice, which may harm the battery life, and the second on factors that may keep consumers from purchasing this type of vehicle. This research work sought to answer these two questions, using a methodology from data science and statistical analysis applied to three surveys carried out on electric vehicle owners. The results allowed us to conclude that, except for the Year variable, all other factors had a marginal effect on the vehicles’ absolute autonomy degradation. Regarding obstacles of the adoption of electric vehicles, the biggest encountered was the insufficient coverage of the network of charging stations.

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“…Other advanced techniques are based on Kalman Filter [7] or on artificial intelligence [8]. They are very accurate but require a high computational effort [6].…”

Section: Introductionmentioning

confidence: 99%

An experimental validation of the adoption of dc-dc converters for the impedance measurement in Li-Ion batteries

Zilio

Mattavelli

2021

2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Syst

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Electrochemical Impedance Spectroscopy (EIS) is one possible technique to determine the State of Health (SOH) in Li-Ion batteries. This article describes some challenges involved in the implementation of EIS analysis in a battery charger. As an application example, some design issues on the control of power converters that can be used to perform the EIS analysis are addressed. The description focuses on several aspects, from the development of the measurement channels for current and voltage to the design of the perturbation signal control system. The device performances are tested in several conditions such as to determine the impedance of a singular Li-ion cell having 3.63 V and 2.6 Ah , but also in a small-scale battery pack having 25.2 V and 11.2 Ah, using different perturbation signals.

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Data-Driven State of Health Estimation of Li-Ion Batteries With RPT-Reduced Experimental Data

Cited by 41 publications

References 19 publications

A Composite Single Particle Lithium-Ion Battery Model Through System Identification

A Composite Single Particle Lithium-Ion Battery Model Through System Identification

Mining Electric Vehicle Adoption of Users

An experimental validation of the adoption of dc-dc converters for the impedance measurement in Li-Ion batteries

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