We report the through-plane thermal conductivities of the several widely used carbon porous transport layers (PTLs) and their thermal contact resistance to an aluminum polarization plate. We report these values both for wet and dry samples and at different compaction pressures. We show that depending on the type of PTL and the existence of residual water, the thermal conductivity of the materials varies from $0.15WK−1m−1$ to $1.6WK−1m−1$, one order of magnitude. This behavior is the same for the contact resistance varying from $0.8m2KW−1$ to $11×10−4m2KW−1$. For dry PTLs, the thermal conductivity decreases with increasing polytetrafluorethylene (PTFE) content and increases with residual water. These effects are explained by the behavior of air, water, and PTFE in between the PTL fibers. It is also found that Toray papers of differing thickness exhibit different thermal conductivities.

Understanding and mitigating the degradation of batteries is important for financial as well as environmental reasons. Many studies look at cell degradation in terms of capacity losses and the mechanisms causing them. However, in this study, we take a closer look at how degradation affects heat sources in batteries, thereby requiring dynamic cooling strategies for battery systems throughout the battery life. In this work, we have studied and compared reversible (entropy-related) and non-reversible heat sources in a commercial LCO-graphite lithium-ion battery (LIB) alongside measuring the surface temperature as a function of the State of Health (SoH). In addition, we studied the effect of different thermal management strategies on both degradation and cooling efficiency. We found that entropic heating plays a major role in overall heat generation. This causes large variations in heat generation and battery temperature over both State of Charge (SoC) and charge versus discharge. The maximum battery temperature increases when the cell degrades as irreversible heat generation increases. Temperature variations over the cell thickness are substantial and increase drastically when the cell degrades. In addition, significant increases in thickness were observed as a result of cell degradation. Furthermore, cycling at elevated temperatures resulted in a larger thickness increase with significant gas production.

This paper presents entropy measurements for a large set of commercial Li-ion cells. We present entropy data on full cells with a variety of common Li-ion cell electrode chemistries; graphite, hard carbon, lithium-titanium-oxide (LTO), lithium cobalt-oxide (LCO), nickel manganese cobalt oxides (NMC), nickel cobalt aluminium oxide (NCA), lithium iron-phosphate (LFP), as well as electrodes with mixes of these. All data were collected using an accelerated potentiometric method in steps of approximately 5% State-of-Charge (SoC) across the full SoC window. We observe that the entropy profiles depend on the chemistry of the Li-ion cells, but that they also vary between different commercial cells with the same chemistry. Entropy contributions are quantified with respect to both, their means, positive and negative contributions as well as their SoC variation. In addition, we present how different cyclic ageing temperatures change the entropy profiles for a selected commercial Li-ion cell through ageing. A clear difference in entropy profiles is observed after a capacity loss of 20%. This difference can be attributed to different ageing mechanisms within the Li-ion cells, leading to changes in the balancing of electrodes, as well as changes in the electrode materials.

Emerging large battery energy storage systems (BESSs) are key enablers in the electrification of the shipping sector. With huge government investments in BESSs, there are large gaps between the government supported BESS initiatives and actual BESS integration results on vessels. This study aims to close these gaps, allowing BESSs to become the preferred solution for ship owners without needing government support. Firstly, this industry-driven study reviews both the industrial approaches to achieve CO₂ emission reductions and the fuel savings and emission reductions from 500 BESS installations on various vessels. Secondly, a 630 kWh BESS retrofitted onto a hybrid-electric vessel is used to quantitively identify the improvement requirements for installations and operations. The installations required many custom designs that were expensive and have high failure risks. The standardization of interfaces’ between BESSs and vessels is thus urgently required. The BESS was intended for spinning reserve capacity and peak shaving but in practice was under-used in terms of energy throughput (shallow cycles and low equivalent full cycles of 80 versus the design specification of 480 yearly). Thirdly, this study develops new, integrated BESS operational models by learning from large operational data, balancing BESS degradation against fuel saving and utilizing onshore/offshore green power supply/charging. The R&D of BESS is required to deal with the increasing safety requirements and further CO₂ emission reductions. Finally, four BESS acceleration scenarios were established to facilitate the technical and operational transferability through utilizing digitalization.

This paper presents the concept of applying incremental capacity analysis (ICA) on the OCV curve in the SoC space. The OCV curve can be obtained from any sequence of discharge or charge current or power pulse with a necessary rest period to allow the cell to reach a pseudo-OCV after each pulse. With a high resolution (>100 pulses) in the full SoC window, an OCV-vs.-SoC curve can be obtained with sufficient accuracy to perform an ICA on the obtained OCV curve. ICA as a diagnostic technique has commonly been applied on Li-ion cells with constant charge and discharge at slow currents. However, a slow controlled constant current charge or discharge is normally not feasible and cannot be easily applied to a battery in an application. Here, we revisit pulse-based ICA to supplement the conventional constant-current-based technique. Based on actual ageing data, we show that ICA performed on a selection of high-resolution OCV curves is comparable or better than conventional ICA with constant current. The main advantage of OCV-ICA is that it can be applied to most cells and systems without a significant interruption of normal cell operation. OCV-ICA can provide valuable insights into ageing mechanisms as well as, e.g., detailed information on changes in internal resistance.