Especially for material combinations incorporating silicon-graphite anodes and nickel-rich cathodes, lifetime and energy density have to be balanced appropriately. In particular, silicon-graphite anodes show increased aging effects due to the extensive volume expansion of silicon and even small variations of its content lead to significant changes in the cell properties because of its large specific capacity. Two batches of the same cell, which differ slightly in their silicon content, were investigated using various charging profiles for a temperature range from 0 °C to 40 °C. The total number of EFC of both cell batches was shown to be strongly dependent on temperature. In addition, cells with reduced silicon content showed EFCs three times higher than their higher silicon counterparts. Contrary to expectations, an extended CV-charging sequence led to an increase in EFC and a decrease in variance. The exclusion of critical voltage ranges shows the most significant influence on both the total of EFC and the variance between the cells. As a result, to increase cell lifetime it is recommended that cells should be preconditioned at low ambient temperatures and extended CV-charging sequences should be considered. If the operational strategy allows the reduction of the upper-voltage-limit, critical voltage areas should be avoided.

The often-observed current distribution between parallel-connected lithium-ion cells within battery modules is probably evoked by the properties of the connection, inhomogeneous contact and power line resistances, the impedance behavior of single cells and of the DoD. The extent to which each of the contributors and the interaction between them affects the current distribution within the battery module is crucial to improve the system’s efficiency, which is investigated here via various electrically cross-linked, physicochemical-thermal simulations with variable system terminal (ST). Consequently, cross-connectors balance the system and reduce DoD shifts between cells. Furthermore, if one compares ST-side and ST-cross, the position of the ST is negligible for topologies that incorporate at least two cells in serial and parallel. Depending on the ST configuration, point and axis symmetry patterns appear for the current distribution. Compared to welding seam and cross-connector resistances, the string connector resistance dominates the current distribution. Like the behavior of a single cell, the system’s rate capability shows a non-linear decrease with increasing C-rate under constant current discharge. As a recommendation for the assembly of battery modules using multiple lithium-ion cells, the position of the ST is of minor importance compared to the presence of cross-connectors and low-resistance string connectors.

Aging behavior and long-term cell-to-cell variations have been much more frequently investigated in single-cells than cells connected in parallel. In particular, the literature lacks a study investigating the aging behavior of cells in parallel that is based on defined cell-to-cell variations and on the results of a previous single-cell aging study. Moreover, present studies are unable to exclude the impacts of measurement systems on their final results. To counter this deficiency, a novel 4-wire measurement technique is used which does not influence the current distribution but allows both single and parallel measurements to be recorded without changing the measurement configuration. Cells in parallel generally displayed improved aging behaviors in comparison to those seen in the single-cell aging study and the positive influence of extended CV-charging was evident, as long as the CV-charging phase was limited in length. It was also observed that the exclusion of critical voltage ranges exerted the most significant influence on the aging rate and dominates the influence of initial cell-to-cell variations in the long-term. As a result, it is recommended that module manufacturers reduce the effort spent on initial cell matching strategies for cells in parallel in favor of developing cell-specific charging profiles.

Range anxiety is one of the leading reasons why people buy conventional cars instead of battery electric vehicles (BEVs). At the same system voltage, an increase in range can be achieved by both higher cell capacities and parallel connection of cells. As cells with sufficient capacity still lack market maturity, parallel connection is currently the remaining alternative for car manufacturers. In parallel-connected lithium-ion battery packs, varying internal cell impedance, different contact resistances or an uneven state of health (SOH) of the cells cause inhomogeneous current distributions within interconnected lithium-ion-batteries (LIBs). However, varying system terminals, different connecting strategies, as well as the number of serial and parallel connections have a major impact on the inhomogeneity of the current distribution. The resulting path resistance of the parallel-connected cells combines all of these influences and is the key to reduce such inhomogeneous current distributions. The extent to which each of the contributors and the interaction between them affects the path resistance within the battery module is crucial to improve both the manufacturing process and the system’s efficiency. In this study, the influence of the stated reasons on the path resistance of parallel-connected LIBs within a battery pack is analyzed, using physicochemical, electrical, and thermal coupled models. Experimental data of the commercially available cylindrical lithium-ion cell LG INR18650MJ1 was used for parameterization and validation of the physicochemical and thermal model. The cell incorporates NMC-811 as cathode active material as well as silicon doped graphite (SiC) on the anode side, which is a promising high energy material combination for future BEVs. To ensure a high practical applicability, the investigated system topologies were restricted from 1s2p to 4s4p. Due to limited installation space, the system terminals often cannot be freely chosen, which is why the positon of the system terminals were varied between side, middle and cross connections. Additionally, the influence of different linking strategies between the serial- and parallel-connected strings was examined. An example of a resulting current distribution for a battery pack with 4s4p topology, using cross- connectors between serial- and parallel-connected LIBs as well as cross-connection of the system terminals is shown in Fig. 1. Part a) illustrates the schematic diagram, while the current distribution is shown in part b). For side connection the system terminal next to cell c4,4 would switch to cell c4,1. As a result, axis and point (see Fig. 1) symmetry patterns within the battery modules could be recognized, depending on the number of serial- and parallel-connected cells and the choice of the system terminals. Furthermore, the presence of cross-connectors leads to equivalent current distributions within the analyzed systems, regardless of whether the system terminals were contacted on the side or crosswise. For car manufacturers, this implicates another level of freedom, since the presence of cross-connectors allows choosing the positon of the system terminals without negative impacts on the current distribution. Additionally, the analyses of different contact resistances showed that particular attention has to be paid to string connectors during the assembling process of battery modules. On the other hand, the impacts of welding spot resistances and cross-connector resistances on the path resistance cannot be neglected by the car manufacturers, but are of minor importance compared to the influence of string connector resistances and the presence of cross-connectors. Current studies therefore focus on verifying these results using measurement data. In particular, the voltage response of parallel-connected cells is considered as an indicator for uneven path resistance, since measurement data of inhomogeneous current distributions are usually missing within battery modules. Furthermore, the influence of varying path resistances on the aging behavior of interconnected LIBs could be of great interest to car manufacturers and has therefore to be investigated in further studies. The results presented were achieved in association with an INI.TUM project, funded by AUDI AG. Figure 1

Due to its high gravimetric and volumetric capacity, silicon is a promising candidate as a new anode material for lithium-ion batteries. In studies over the last two decades, silicon has been investigated in various designs such as silicon nanowires, silicon thin films, silicon wafers, or silicon nanoparticles. Silicon is also found in commercially available cells, both as a pure-silicon anode as well as a silicon-graphite composite anode. In addition to experiments, lithium-ion batteries containing conventional anode materials like graphite as well as novel anode materials like silicon are also studied simulatively. Various modeling approaches for lithium-ion batteries can be found in the literature. Focusing only on physicochemical approaches, the Newman model and its variations are the most widely used for conventional material combinations. However, the literature does not provide any physicochemical modeling approach tailored specifically to alloying reactions that provides the same insight into the battery as the Newman model does. Thus, the question arises whether classical models such as the Newman model can also be applied to lithium-ion batteries with pure-silicon anodes. To examine whether the Newman model can provide accurate results even for pure-silicon anodes, we parameterized a classical Newman model for a lithium-ion battery with a pure-silicon anode and a nickel cobalt aluminum oxide (NCA) cathode. The silicon anode consists of 70 wt% silicon, 20 wt% graphite, and 10 wt% binders and additives. However, the graphite is considered electrochemically inactive. The parameterization is based on values from a) the electrode manufacturing process (e.g., initial porosity, coating thickness), b) measured values (e.g., open-circuit potentials), and c) literature data (e.g., exchange current density, solid-phase diffusivity). For parameterization, we used laboratory cells in CR2023 coin cell format with a capacity of about 5 mAh. The model was validated using 3 mAh Swagelok T-cells with an three-electrode setup using a lithium-metal reference as well as custom-built large-format 5 Ah multilayer pouch cells. The simulation results of CC-CV charge and discharge processes at different current rates show good agreement with measurements with a root-mean-squared error of about 22 mV at a current rate of C/10 (see Figure a), and less than 5% deviation in discharge capacity at a current rate of 2C (see Figure b). Overall, the Newman model appears to be a viable choice for pure-silicon anodes as well. However, care must be taken in parameterization. A literature review revealed that material parameters such as the exchange current density can vary by up to 13 orders of magnitude. In addition, reconstruction of the full-cell potential via half-cell potentials is of paramount importance when using partially lithiated materials, since the degree of lithiation does not necessarily approach the 0 and 1 limits. For the deliberately partially lithiated silicon used in our study, we found the utilization to be between 0.04 and 0.31, thus, a comparison between measurements and simulations during the crystallization process in the fully lithiated state is not possible. Discharge tests with multilayer pouch cells showed that the temperature rise cannot be neglected and might become rate-limiting at even higher current rates, while the discharge capacity shows that the electrode kinetics is most likely not rate-limiting. Since simulation studies are a cost-effective method for designing new cells, our results are of practical importance. Demonstrating that the Newman model is applicable not only to conventional intercalation materials such as graphite but also to cells containing a pure-silicon alloy material with micrometer-sized particles may encourage more researchers to simulatively explore novel electrode materials. However, in general, any model and parameterization should be validated by experiments. Figure 1