State of Charge and State of Health Estimation of Lithium-Ion Batteries

Buchman, Attila; Lung, Claudiu

doi:10.1109/siitme.2018.8599196

Cited by 11 publications

(3 citation statements)

References 7 publications

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“…When installing solar-storage systems, the literature mostly recommends that the battery capacity should be chosen while ensuring that the battery does not deplete its capacity below 50 percent. This rule-of-thumb is advised not to damage the battery terminals, which worsens the battery's state-of-health and, thus, shortens the battery's lifetime [58]. Based on our study, we find that, in hot climates, specifying a lower minimum state of charge can still satisfy the reliability considerations while achieving a lower net present cost.…”

Section: Discussionmentioning

confidence: 76%

State-of-Charge Effects on Standalone Solar-Storage Systems in Hot Climates: A Case Study in Saudi Arabia

Elshurafa

Aldubyan

2019

Sustainability

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In this paper, we quantify the economic and environmental implications of operating a standalone photovoltaic-battery system (PVB) while varying the battery’s minimum allowable state of charge (MSOC), the load profile, and simultaneously incorporating ambient temperature effects in hot climates. To that end, Saudi Arabia has been chosen for this case study. Over a project lifetime of 25 years, we find that, contrary to the widely accepted norm of 50% being a reasonable MSOC, a lower MSOC can bestow economic benefits. For example, a MSOC of 20% results in a lower number of batteries required throughout the lifetime of the project—while still meeting demand. For a village of 1000 homes, this translates to a saving of $47 million in net present value. Further, incorporating temperature effects results in deducing more realistic costs that are 125% higher than the ideal scenario (i.e., when temperature is not modeled). This difference stems from underestimating the actual number of batteries needed throughout the project lifetime. Compared to a diesel-powered microgrid, and for a village of 1000 homes, a PVB would, on an annual basis, avoid emitting 5000 tons of carbon and avoid burning 2 million liters of diesel.

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Section: Discussionmentioning

confidence: 76%

State-of-Charge Effects on Standalone Solar-Storage Systems in Hot Climates: A Case Study in Saudi Arabia

Elshurafa

Aldubyan

2019

Sustainability

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“…In the classical battery state estimation method, the battery state is estimated by directly measuring the current and voltage [6], [9]. The SOC can be calculated by measuring the terminal voltage and open-circuit voltage (OCV), or by the current integration method.…”

Section: A Classical Battery State Estimation Methodsmentioning

confidence: 99%

Bayesian Estimation of Model Parameters of Equivalent Circuit Model for Detecting Degradation Parts of Lithium-Ion Battery

et al. 2021

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Nowadays, the use of electric vehicles is increasing leading to a growing demand for more efficient use of lithium-ion batteries. The state-of-charge (SOC) has been estimated in previous studies to optimize energy management of batteries. For more efficient battery utilization, detecting degradation is important. However, it is difficult for conventional methods to distinguish the effect of the model parameters including different time constants. Identifying model parameters of multiple RC parallel branches, which represent the impedance of wider frequency ranges, is a necessary requirement to detect the degradation of parts. In this study, we present a method for estimating the model parameters of multiple RC parallel branches. We designed the Markov Chain Monte Carlo algorithm by setting a search range limit and moving window, which enable estimation of the model parameters of parallel branches of different time constants. Through validation of the algorithm based on simulation, the model parameters of a third-order circuit were estimated to be within the error range of 15.2 %. In addition, impedance was calculated from the estimated model parameters in the test using a real battery dataset. The error of impedance was less than 10 % from 0.01 to 100 Hz which was sufficiently low to monitor the change of the parameters owing to degradation. As the impedance in the high-frequency band above 0.1 Hz is more likely to change because of degradation, the proposed method can be used to monitor the model parameters that change as a result of degradation.INDEX TERMS Battery management systems, Bayes methods, detection of battery degradation parts, equivalent circuit model

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“…We can view this parameter as a thermodynamic quantity that enables us to assess the battery's potential energy. From the SOC, we can estimate the state of health (SOH) [26] because SOC is the main task of a battery management system. The existing SOC can be categorized as direct and indirect: the direct point to the remaining capacity, using the online integration.…”

Section: Soc Calculationmentioning

confidence: 99%

Memristive Equivalent Circuit Model for Battery

Mogadem

2021

Sustainability

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The design of mathematical models is based on conservation laws and also on the fundamental principles of modeling: structure, parameters, and physical meaning. Those kinds of modeling should have specific capabilities to deal with different working conditions and environments coping with challenges that include but are not limited to battery capacity, life-cycle, or the attempts to manipulate the current profiles during operation. Introducing memristive elements in batteries will be ideal to satisfy these fundamentals and goals of modeling, whereas addressing the recycling and sustainability concerns on the environmental impact by the placement of TiO2 memristor into this model can promote a recovery hierarchy via recycling and dispatching a slight amount to disposal as the previous focus was mainly concentrated on availability. As for battery materials, modeling, performing, and manufacturing all have proliferated to grasp the possible sustainability challenges inherited in these systems. This paper investigated electrochemical impedance spectroscopy to study this model and the dynamic behavior inside the battery. We found a solution to address the existing battery limitations that elucidate the battery degradation without affecting the performance, correspondingly by employing the dampest least-squares combination with nonlinear autoregressive exogenous for identifying such model and its associated parameters because of its embedded memory and fast convergence to diminish the influence of the vanishing gradient. Lastly, we found that this model is proven to be efficient and accurate compared to actual experimented data to validate our theory and show the value of the proposed model in real life while assuming Normal Gaussian distribution of data error with outstanding results; the auto-correlations were within the 95% confidence limit, the best validation was 2.7877, and an overall regression of 0.99993 was achieved.

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State of Charge and State of Health Estimation of Lithium-Ion Batteries

Cited by 11 publications

References 7 publications

State-of-Charge Effects on Standalone Solar-Storage Systems in Hot Climates: A Case Study in Saudi Arabia

State-of-Charge Effects on Standalone Solar-Storage Systems in Hot Climates: A Case Study in Saudi Arabia

Bayesian Estimation of Model Parameters of Equivalent Circuit Model for Detecting Degradation Parts of Lithium-Ion Battery

Memristive Equivalent Circuit Model for Battery

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