Sensorless battery temperature measurements based on electrochemical impedance spectroscopy

Raijmakers, L.H.J.; Danilov, Dmitri L.; Lammeren, van Jpm; Lammers, Mjg; Notten, Phl Peter

doi:10.1016/j.jpowsour.2013.09.005

Cited by 157 publications

(117 citation statements)

References 22 publications

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“…The impedance phase shift is another important parameter in the EIS test. Our previous work [20] has presented evidence for the existence of the intrinsic relationship between measured impedance phase shift and the internal cell temperature with electrochemical equilibrium, which is seldom influenced by battery degradation for an 8-Ah LiFePO 4 battery. Raijmakers et al [4] also put forward an intercept frequency which was extracted from impedance spectra of a Li(NCA)O 2 and a LiFePO 4 battery and exclusively related to the internal battery temperature based on EIS.…”

Section: Introductionmentioning

confidence: 98%

“…Our previous work [20] has presented evidence for the existence of the intrinsic relationship between measured impedance phase shift and the internal cell temperature with electrochemical equilibrium, which is seldom influenced by battery degradation for an 8-Ah LiFePO 4 battery. Raijmakers et al [4] also put forward an intercept frequency which was extracted from impedance spectra of a Li(NCA)O 2 and a LiFePO 4 battery and exclusively related to the internal battery temperature based on EIS. As aforementioned, the impedance-based temperature estimation methods eliminate the requirements of too many hardware temperature sensors and knowledge of the cell thermal properties [4,[17][18][19].…”

Section: Introductionmentioning

confidence: 98%

“…Surface mounted thermal sensors (thermistors and thermocouples) suffer from heat transfer delay due to the thermal mass of batteries. In consequence of cell thermal non-equilibrium, the internal temperature differs from the external counterpart [4]. It is complicated to directly measure the internal temperature of large format batteries in the vehicular application.…”

Section: Introductionmentioning

confidence: 99%

“…Raijmakers et al [4] also put forward an intercept frequency which was extracted from impedance spectra of a Li(NCA)O 2 and a LiFePO 4 battery and exclusively related to the internal battery temperature based on EIS. As aforementioned, the impedance-based temperature estimation methods eliminate the requirements of too many hardware temperature sensors and knowledge of the cell thermal properties [4,[17][18][19]. Battery SoC and health often visibly change and several effective estimation strategies considering uncertain driving conditions for EVs and HEVs have been presented [21][22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

“…The experiment results indicated the high estimation accuracy and strong robustness of the method to the model uncertainty and measurement noise. The impedance-based temperature estimation method reveal that there is a certain frequency which is distinctly dependent on the temperature but does not depend on SoC and battery aging state for the LiFePO 4 battery [4,20], which is helpful to implement the impedance-based temperature method from lab to online application in consequence of methods capable of measuring impedance spectra using existing power electronics [27,28].…”

Section: Introductionmentioning

confidence: 99%

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Battery Internal Temperature Estimation for LiFePO4 Battery Based on Impedance Phase Shift under Operating Conditions

et al. 2017

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An impedance-based temperature estimation method is investigated considering the electrochemical non-equilibrium with short-term relaxation time for facilitating the vehicular application. Generally, sufficient relaxation time is required for battery electrochemical equilibrium before the impedance measurement. A detailed experiment is performed to investigate the regularity of the battery impedance in short-term relaxation time after switch-off current excitation, which indicates that the impedance can be measured and also has systematical decrement with the relaxation time growth. Based on the discussion of impedance variation in electrochemical perspective, as well as the monotonic relationship between impedance phase shift and battery internal temperature in the electrochemical equilibrium state, an exponential equation that accounts for both measured phase shift and relaxation time is established to correct the measuring deviation caused by electrochemical non-equilibrium. Then, a multivariate linear equation coupled with ambient temperature is derived considering the temperature gradients between the active part and battery surface. Equations stated above are all identified with the embedded thermocouple experimentally. In conclusion, the temperature estimation method can be a valuable alternative for temperature monitoring during cell operating, and serve the functionality as an efficient implementation in battery thermal management system for electric vehicles (EVs) and hybrid electric vehicles (HEVs).

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Battery Internal Temperature Estimation for LiFePO4 Battery Based on Impedance Phase Shift under Operating Conditions

et al. 2017

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Porous Electrode Modeling and its Applications to Li‐Ion Batteries

Chen

Danilov

Eichel

et al. 2022

Advanced Energy Materials

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Figure 12. a-c) Schematic representation of the electrode potential at electrode/electrolyte interfaces. [145] Red areas indicate the electrode region and blue the electrolyte region. a) The Butler-Volmer approach does not consider charges at the interface. b) More detailed representation of the electrode/ electrolyte interface, considering specifically adsorbed species (green area) and screening counter charges at the surface of the electrode (dark red) and in the electrolyte (dark blue). c) Reduced electrode/electrolyte interface considering the surface charge in the electrode and screening charge in the electrolyte. d) Typical examples of impedance spectra for a porous electrode with insertion-type reactions. [151] Impedance simulations of porous graphite electrodes in contact with electrolyte with e) various particle sizes and f) electrode porosities. [152] a-c) Reproduced with permission. [145]

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Data‐Driven–Based Internal Temperature Estimation for Lithium‐Ion Battery Under Variant State‐of‐Charge via Electrochemical Impedance Spectroscopy

et al. 2022

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Internal temperature estimation is critical to the safe operation of lithium‐ion batteries (LIBs), and electrochemical impedance spectroscopy (EIS)‐based methods have been demonstrated to be promising. However, accurate internal temperature estimation under variant state‐of‐charge (SoC) is still challenging due to the combined impact of temperature and SoC on the EIS. Accordingly, this work proposes a novel EIS‐based internal temperature estimation approach, for which SoC‐insensitive EIS features are quantitatively selected and utilized for temperature estimation using support vector regression (SVR) with unknown SoC. First, the EIS feature selection is performed to select SoC‐insensitive features from the imaginary of impedance spectrum. Subsequently, an SVR‐based framework and a well‐trained SVR model are created to estimate the internal temperature of LIBs. The performance of the proposed model is validated by its lowest estimation error (0.57 °C) under known and unknown SoCs compared to that of the existing methodologies. The results confirmed that the proposed method holds the advantage in estimating the internal battery temperature with different SOCs.

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Sensorless battery temperature measurements based on electrochemical impedance spectroscopy

Cited by 157 publications

References 22 publications

Battery Internal Temperature Estimation for LiFePO4 Battery Based on Impedance Phase Shift under Operating Conditions

Battery Internal Temperature Estimation for LiFePO4 Battery Based on Impedance Phase Shift under Operating Conditions

Porous Electrode Modeling and its Applications to Li‐Ion Batteries

Data‐Driven–Based Internal Temperature Estimation for Lithium‐Ion Battery Under Variant State‐of‐Charge via Electrochemical Impedance Spectroscopy

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