A mathematical model is presented for a complete lithium-sulfur cell. The model includes various electrochemical and chemical ͑precipitation͒ reactions, multicomponent transport phenomena in the electrolyte, and the charge transfer within and between solid and liquid phases. A change in the porosity of the porous cathode and separator due to precipitation reactions is also included in the model. The model is used to explain the physical reasons for the two-stage discharge profiles that are typically obtained for lithium-sulfur cells.

A thermal model for a lithium-ion cell is presented and used to predict discharge performance at different operating temperatures. The results from the simulations are compared to experimental data obtained from lithium-ion pouch cells. The model includes a set of parameters ͑and their concentration and temperature dependencies͒ that has been obtained for a lithium-ion cell composed of a mesocarbon microbead anode, LiCoO 2 cathode in 1 M LiPF 6 salt, in a mixture of ethylene carbonate, propylene carbonate, ethyl-methyl carbonate, and diethyl carbonate electrolyte. The parameter set was obtained by comparing the model predictions to the experimental discharge profiles obtained at various temperatures and rates. The concentration and temperature dependence of the extracted parameters were correlated through empirical expressions. Also, the effect of including the thermal dependence of various parameters in the model on the simulated discharge profiles is discussed.

The primary mechanisms limiting lithium sulfur (Li-S) cell cycle life and thermal stability are discussed. Two major cycle life limiting mechanisms are identified: development of rough surface morphology on the metallic lithium anode with cycling; and depletion of lithium and electrolyte components through chemical reaction. The approach taken here to mitigate these problems, by employing physical protection, including multi-functional membrane assemblies and non-isotropic pressure is presented. Sulfur utilization of 92%, at C/5 discharge rates, increased cycle life and elimination of thermal runaway in 300 mAh Li-S cells was achieved.

Lithium-ion pouch cells were cycled at five different temperatures ͑5, 15, 25, 35, and 45°C͒, and rate capability studies were performed after every hundred cycles. The data were used with a simple physics-based model to estimate parameters that capture the capacity fade in the cell, with cycling. The weight of active material within each electrode was estimated as a function of time, using rate capability data at the C/33 rate. The C-rate for these cells is 1.656 A. The capacity fade due to the loss of active material and that due to the loss of cyclable lithium were quantified. It was found that while the loss of cyclable lithium is the limiting cause for the capacity decay of the cell during the first 200 cycles, the loss of active carbon, which is the anode material, becomes limiting for these cells. The loss of active material leads to a drastic decrease in cell capacity at higher temperatures.

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A set of parameters (and their concentration and temperature dependences) has been obtained for a lithium-ion battery composed of a MCMB anode, LiCoO 2 cathode in 1M LiPF 6 in a mixture of ethylene carbonate (EC), propylene carbonate (PC), ethyl-methyl carbonate (EMC) and di-ethyl carbonate (DEC) electrolyte. The parameter set was obtained by comparing the model simulations to the experimental discharge profiles obtained at various temperatures and rates. The concentration and temperature dependence of the extracted parameters were correlated through empirical expressions. These correlations can be used to predict the discharge process of a lithium-ion battery for different charge/discharge rates and temperatures. IntroductionThe comparison of experimental charge and discharge data with mathematical models helps battery engineers, first, to understand how various parametersthermodynamic, kinetic and design -determines the performance of the battery under various operating condition like charge / discharge rate, temperature etc and then to use the model along with the parameters determined from the above comparison to explore the performance of the battery under different operating conditions thus reducing the number of time consuming experiments required. Such comparisons have been made for batteries of various chemistries (1,2,3,4,5) and the estimated parameters have been used in optimizing those batteries for different intended end uses. In all of the above, the comparisons have been done for experimental data only at a single temperature using isothermal model. Experimentally obtained correlations were used in them to describe the concentration dependence of the liquid phase ionic conductivity only. Temperature and concentration dependence of other transport properties like salt diffusion coefficient, transference number and mean molar activity of salt have been neglected in most of the existing models.

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