Analysis of the heat generation of lithium-ion battery during charging and discharging considering different influencing factors

Liu, Guangming; Ouyang, Minggao; Lu, Languang; Li, Jianqiu; Han, Xiao

doi:10.1007/s10973-013-3599-9

Cited by 189 publications

(99 citation statements)

References 27 publications

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“…As a complex electrochemical component, the battery impedance is strongly influenced by operating conditions. Although the present temperature influence on the impedance could be revealed by real time parameter adaptation in AEP, the future temperature variation due to battery ohmic and entropic heat generation [41] could not be determined at the present moment. In order to predict the parameter change owing to temperature variation on the PH, a battery heat generation/dissipation model is required to predict the future temperature change, leading to a certain increase in computational load.…”

Section: Explanation Of Different Model Parameter Determination Appromentioning

confidence: 99%

A highly accurate predictive-adaptive method for lithium-ion battery remaining discharge energy prediction in electric vehicle applications

Liu

Ouyang

et al. 2015

Applied Energy

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Section: Explanation Of Different Model Parameter Determination Appromentioning

confidence: 99%

A highly accurate predictive-adaptive method for lithium-ion battery remaining discharge energy prediction in electric vehicle applications

Liu

Ouyang

et al. 2015

Applied Energy

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“…As shown in Table ,

\frac{\partial E_{OCV}}{\partial T}

can be calculated based on the measurement of the change of E OCV under variant temperature. Note that the decrease of E OCV induced by self‐discharge is obvious under high SOC and elevated temperature, the variation of voltage within the temperature change interval should be compensated based on the voltage drop in the previous temperature

Q_{italicgen 1}^{'} = \frac{I^{2} ∙ ((), R_{ohm} + R_{pol}) + I ∙ T ∙ \frac{\partial E_{OCV}}{\partial T}}{V_{italicbat}}

…”

Section: Model Developmentmentioning

confidence: 99%

“…Note that the decrease of E OCV induced by self-discharge is obvious under high SOC and elevated temperature, the variation of voltage within the temperature change interval should be compensated based on the voltage drop in the previous temperature. 42 Q 0 gen1 =…”

Section: Thermal Modelmentioning

confidence: 99%

Thermal safety study of Li‐ion batteries under limited overcharge abuse based on coupled electrochemical‐thermal model

et al. 2020

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Summary Many fire accidents of electric vehicles were reported that happened during the charging process. In order to investigate the reasons that lead to this problem, this paper studies the thermal safety of Li‐ion batteries under limited overcharge abuse. A 3D electrochemical‐thermal coupled model is developed for modeling thermal and electrochemical characteristics from normal charge to early overcharge state. This model is validated by experiment at charge rates of 0.5C, 1C, and 2C. The simulation results indicate that irreversible heat contributes most to temperature rise during the normal charge process, but the heat induced by Mn dissolution and Li deposition gradually dominates heat generation in the early overcharge period. Based on this, a threshold selection method for multistage warning of batteries overcharge is proposed. Among them, level 1 should be considered as a critical stage during the early overcharge process due to the deposited lithium starts to react with electrolyte at the end of level 1, where temperature rate increases to 0.5°C min−1 for 1C charge. While the thresholds of levels depend on charge rate and composition of battery. Furthermore, several critical parameters are analyzed to figure out their effects on thermal safety. It is found that the temperature at the end of overcharge is significantly influenced by the change of positive electrode thickness and solid electrolyte interface (SEI) film resistance. The final temperature increases by 17.5°C and 7.9°C, respectively, with positive electrode thickness ranging from 50 to 80 μm and SEI film resistance increasing from 0.002 to 0.03 Ω.

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“…It is well known that the heat generation within a Li-ion battery cell is not constant for a given current. According to Liu et al [16], the generated heat consists of joule heat and reaction heat, which are both dependent, amongst others, on state of charge. However, it can be stated that the system reached a quasi-steady state after about two cycles or after 50 min.…”

Section: Thermal Characterizationmentioning

confidence: 99%

Test Method for Thermal Characterization of Li-Ion Cells and Verification of Cooling Concepts

et al. 2017

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Temperature gradients, thermal cycling and temperatures outside the optimal operation range can have a significant influence on the reliability and lifetime of Li-ion battery cells. Therefore, it is essential for the developer of large-scale battery systems to know the thermal characteristics, such as heat source location, heat capacity and thermal conductivity, of a single cell in order to design appropriate cooling measures. This paper describes an advanced test facility, which allows not only an estimation of the thermal properties of a battery cell, but also the verification of proposed cooling strategies in operation. To do this, an active measuring unit consisting of a temperature and heat flux density sensor and a Peltier element was developed. These temperature/heat flux sensing (THFS) units are uniformly arranged around a battery cell with a spatial resolution of 25 mm. Consequently, the temperature or heat flux density can be controlled individually, thus forming regions with constant temperature (cooling) or zero heat flux (insulation). This test setup covers the whole development loop from thermal characterization to the design and verification of the proposed cooling strategy.

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Analysis of the heat generation of lithium-ion battery during charging and discharging considering different influencing factors

Cited by 189 publications

References 27 publications

A highly accurate predictive-adaptive method for lithium-ion battery remaining discharge energy prediction in electric vehicle applications

A highly accurate predictive-adaptive method for lithium-ion battery remaining discharge energy prediction in electric vehicle applications

Thermal safety study of Li‐ion batteries under limited overcharge abuse based on coupled electrochemical‐thermal model

Test Method for Thermal Characterization of Li-Ion Cells and Verification of Cooling Concepts

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