Thermal Energy Production in an Electrochemical Cell and Heat Transfer to Its Dark Surroundings

The theoretical formulation presented in this abridged paper was developed to predict the transient cell average temperature of a lithium-based cell during its discharge in dark, extremely low material density surroundings where the predominant mechanism of heat exchange between its shroud surface and surroundings is the thermal radiation process for a given cell discharge current and its initial temperature. The average computed temperature of an ideal lithium-based button cell, such as Li(s)/electrolyte/CF(s), is presented as a function of time in the form of plots at two discharge currents as an example of the application of the derived formulation. The presented data are briefly discussed in light of the lithium-based cell component stability and its safe discharge operation.

Thermal Energy Production and Heat Exchange between an Electrochemical Cell and Its Surroundings

The theoretical formulation presented in this paper was developed to predict the cell average temperature as a function of time for a given cell discharge current and its initial temperature under adiabatic and nonadiabatic conditions. The cell average temperature versus time data calculated from the derived formulation is presented in the form of plots for an ideal lithium-based button cell (for example, lithium(s)/electrolyte/carbon monofluoride(s)) during its discharge period. The presented data are briefly discussed in light of cell component stability and safe discharge operation.

Bilevel vs. Passive Equalizers for Second Life EV Batteries

Once lithium-ion batteries degrade to below about 80% of their original capacity, they are no longer considered satisfactory for electric vehicles (EVs), but they are still adequate for second-life energy storage applications. However, once this level is reached, capacity fade increases at a much faster rate, and the spread between the cell capacities becomes much wider. If the passive equalizer (PEQ) from the EV is still used, battery capacity remains equal to that of the worst cell in the stack, just like it was in the EV. Unfortunately, the worst cell eventually becomes much weaker than the cell average, and the other cells are not fully utilized. If operated while the battery is in use, an active equalizer (AEQ) can increase the battery capacity to a much higher value close to the cell average, but AEQs are much more expensive and are not considered cost effective. However, it can be shown that the bilevel equalizer (BEQ), a PEQ/AEQ hybrid, also can provide a capacity very close to the cell average and at a much lower cost than an AEQ.

Characterization of Simultaneous Evolution of Size and Composition Distributions Using Generalized Aggregation Population Balance Equation

The application of multi-dimensional population balance equations (PBEs) for the simulation of granulation processes is recommended due to the multi-component system. Irrespective of the application area, numerical scheme selection for solving multi-dimensional PBEs is driven by the accuracy in (size) number density prediction alone. However, mixing the components, i.e., the particles (excipients and API) and the binding liquid, plays a crucial role in predicting the granule compositional distribution during the pharmaceutical granulation. A numerical scheme should, therefore, be able to predict this accurately. Here, we compare the cell average technique (CAT) and finite volume scheme (FVS) in terms of their accuracy and applicability in predicting the mixing state. To quantify the degree of mixing in the system, the sum-square χ2 parameter is studied to observe the deviation in the amount binder from its average. It has been illustrated that the accurate prediction of integral moments computed by the FVS leads to an inaccurate prediction of the χ2 parameter for a bicomponent population balance equation. Moreover, the cell average technique (CAT) predicts the moments with moderate accuracy; however, it computes the mixing of components χ2 parameter with higher precision than the finite volume scheme. The numerical testing is performed for some benchmarking kernels corresponding to which the analytical solutions are available in the literature. It will be also shown that both numerical methods equally well predict the average size of the particles formed in the system; however, the finite volume scheme takes less time to compute these results.