Fast Estimation of Entropy Profiles for Lithium-Ion Batteries

Abstract

The operating temperature of a lithium-ion battery (LIB) has strong effects on its electrochemical performance, safety, and lifetime. Reliable predictions of cell temperature and heat generation are required for the design and thermal management of battery systems. During the normal operation of LIBs, heat sources can be classified into irreversible heat from resistive losses such as ohmic resistance, charge-transfer overpotentials, and mass-transfer limitations; and reversible heat from entropy change . The irreversible heat generation is related to the cell's internal resistance and the applied current. The reversible heat depends on the entropy variation of electrode materials, the state of charge (SoC), and the temperature. An accurate measurement of entropy-variation will not only help to improve the battery operation under optimal thermal conditions but can also be used to diagnose the battery aging since it can reveal crystal structure changes in the electrodes [1, 2].Techniques for measuring the entropy of a battery can mainly be classified into potentiometric [3] and calorimetric methods. The potentiometric method measures the open circuit voltage (OCV) changes while the cell temperature is varied at different SoCs. This method requires a long relaxation time to obtain the OCV equilibrium state following each SoC point and temperature step. The calorimetric method [4-6] is based on measuring the heat generation during charge and discharge, and various models are applied to differentiate between and quantify the reversible and irreversible heat sources. The entropy variation with SOC is obtained via the reversible heat rate.Recent improved methods include e.g., Schmidt et al. [4] who proposed a reversible heat extraction method based on electrothermal impedance spectroscopy (ETIS) and Damay et al. [5] proposing a fast calorimetric method to obtain a continuous entropy profile. The cell surface temperature is monitored while the battery is charged and discharged continuously. A thermal balance is used to estimate the heat generation from the monitored cell temperature changes during charge and discharge. The benefit of this method can be low cost, fast and high resolution. Bedürftig et al. [6] proposed a calorimetric method named ‘Double Pulse Method’ to measure reversible heat in lithium-ion battery cells by exciting the cell with charge and discharge current pulses.Here we present a new entropy characterization method via charge and discharge cycles of a LIB at low constant C-rates using simple insulating condition. Through monitoring the variations of cell surface temperature and voltage with the state of charge, the continuous variation of entropy with the state of charge can be extracted. These results were compared to classical entropy measurements obtained through the potentiometric method as shown in Figure 1. In addition, the extracted entropy variation data is input into a LIB modelling approach, combining a P2D-electrochemical sub-model for battery operation and a 3D-finite-element sub-model for thermal behavior while battery charge and discharge. The model predictions on the cell outer surface temperature variation while charge and discharge under different C-rates are compared with the data obtained in the battery characterization tests as shown in Figure 2. Good agreements between the model predictions and tests are achieved.