A Review on Temperature-Dependent Electrochemical Properties, Aging, and Performance of Lithium-Ion Cells

Alipour, Mohammad; Ziebert, Carlos; Conte, Fiorentino Valerio; Kizilel, Rıza

doi:10.3390/batteries6030035

Cited by 109 publications

(50 citation statements)

References 206 publications

(258 reference statements)

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“…The accuracy of SOC estimation is affected by many factors such as temperature [29], cells balancing [30,31] and OCV value [27]. In this work, considering the complexity of the model and the limitations of the experimental condition, only SOC is regarded as a non-linear function of OCV.…”

Section: Relationship Between Soc and Ocvmentioning

confidence: 99%

State of Charge Estimation of Lithium Battery Based on Improved Correntropy Extended Kalman Filter

Duan

Wang

et al. 2020

Energies

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State of charge (SOC) estimation plays a crucial role in battery management systems. Among all the existing SOC estimation approaches, the model-driven extended Kalman filter (EKF) has been widely utilized to estimate SOC due to its simple implementation and nonlinear property. However, the traditional EKF derived from the mean square error (MSE) loss is sensitive to non-Gaussian noise which especially exists in practice, thus the SOC estimation based on the traditional EKF may result in undesirable performance. Hence, a novel robust EKF method with correntropy loss is employed to perform SOC estimation to improve the accuracy under non-Gaussian environments firstly. Secondly, a novel robust EKF, called C-WLS-EKF, is developed by combining the advantages of correntropy and weighted least squares (WLS) to improve the digital stability of the correntropy EKF (C-EKF). In addition, the convergence of the proposed algorithm is verified by the Cramér–Rao low bound. Finally, a C-WLS-EKF method based on an equivalent circuit model is designed to perform SOC estimation. The experiment results clarify that the SOC estimation error in terms of the MSE via the proposed C-WLS-EKF method can efficiently be reduced from 1.361% to 0.512% under non-Gaussian noise conditions.

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Section: Relationship Between Soc and Ocvmentioning

confidence: 99%

State of Charge Estimation of Lithium Battery Based on Improved Correntropy Extended Kalman Filter

Duan

Wang

et al. 2020

Energies

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“…It was stated that there was a significant power loss and capacity decrease below 20°. Alipour et al 23 conducted a review study on temperature‐dependent electrochemical properties, aging and performance of lithium‐ion batteries. They noted that batteries could be affected by temperature, affecting their performance at best, causing security problems at worst.…”

Section: Introductionmentioning

confidence: 99%

Thermal management system with nanofluids for hybrid electric aircraft battery

Yetik

Karakoç

2021

Int J Energy Res

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Electric aircraft should be used more intensively due to the increase in energy consumption and the decrease in reserves of fossil fuels. Batteries are also an important factor in the development of electric aircraft. One of the most important parameters for the effective operation of batteries is the evaluation of heat dissipation. The even distribution or reduction of the heat generated during the operation of lithium-ion batteries extends the life of the batteries and ensures the

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“…[3] between 20 • C and 40 • C, and Refs. [4,5] between 20 • C to 50 • C. Regarding the temperatures gradients within a battery pack, there is, instead, general agreement that differences in the operating temperature of the single cells should not exceed 5 • C [4]. It is, then, apparent that the thermal management of the battery pack is key to ensuring safe operation and avoiding fast degradation of the cell performance.…”

Section: Introductionmentioning

confidence: 99%

“…Based on the results reported in the literature, it is possible to conclude that the adoption of a PCM in the battery pack is not sufficient to maintain cell temperature low enough to preserve their performance and lifetime. In this respect, M. Alipour et al [5] report that, for the majority of Li-ions batteries, the optimal operating range is between 10-35 • C. This work presents the design of a combined active/passive BTM solution for the battery pack of an electric van. The research was carried out in the framework of the European funded project Everlasting, that aims at enhancing the range, the lifetime and the safety of Li-ion batteries through innovative battery management.…”

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confidence: 99%

Experimental and Numerical Investigation of the Thermal Performance of a Hybrid Battery Thermal Management System for an Electric Van

et al. 2021

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The temperature and the temperature gradient within the battery pack of an electric vehicle have a strong effect on the life time of the battery cells. In the case of automotive applications, a battery thermal management (BTM) system is required to maintain the temperature of the cells within a prescribed and safe range, and to prevent excessively high thermal gradients within the battery pack. This work documents the assessment of a thermal management system for a battery pack for an electric van, which adopts a combination of active/passive solutions: the battery cells are arranged in a matrix or composite made of expanded graphite and a phase change material (PCM), which can be actively cooled by forced air convection. The thermal dissipation of the cells was predicted based on an equivalent circuit model of the cells (LG Chem MJ1) that was empirically calibrated in a previous study. It resulted that, in order to keep the temperature of the battery pack at or below 40 °C during certain charge/discharge cycles, a purely passive BTM would require a considerable amount of PCM material that would unacceptably increase the battery pack weight. Therefore, the passive solution was combined with an air cooling system that could be activated when necessary. To assess the resulting hybrid BTM concept, CFD simulations were performed and an experimental test setup was built to validate the simulations. In particular, PCM melting and solidification times, the thermal discrepancy among the cells and the melting/solidification temperatures were examined. The melting time experimentally observed was higher than that predicted by the CFD model, but this discrepancy was not observed during the solidification of the PCM. This deviation between the CFD model results and the experimental data during PCM melting can be attributed to the thermal losses occurring through the mock-up casing as the heating elements are in direct contact with the external walls of the casing. Moreover, the temperature range over which the PCM solidifies was 6 °C lower than that estimated in the numerical simulations. This occurs because the simple thermodynamic model cannot predict the metastable state of the liquid phase which occurs before the onset of PCM solidification. The mockup was also used to emulate the heat dissipation of the cells during a highway driving cycle of the eVan and the thermal management solution as designed. Results showed that for this mission of the vehicle and starting from an initial temperature of the cells of 40 °C, the battery pack temperature could be maintained below 40 °C over the entire mission by a cooling air flow at 2.5 m/s and at a temperature of 30 °C.

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A Review on Temperature-Dependent Electrochemical Properties, Aging, and Performance of Lithium-Ion Cells

Cited by 109 publications

References 206 publications

State of Charge Estimation of Lithium Battery Based on Improved Correntropy Extended Kalman Filter

State of Charge Estimation of Lithium Battery Based on Improved Correntropy Extended Kalman Filter

Thermal management system with nanofluids for hybrid electric aircraft battery

Experimental and Numerical Investigation of the Thermal Performance of a Hybrid Battery Thermal Management System for an Electric Van

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