Imperial College London

Mr Waseem Marzook

Faculty of EngineeringDepartment of Mechanical Engineering

Research Postgraduate







409City and Guilds BuildingSouth Kensington Campus





Publication Type

8 results found

Marzook MW, Hales A, Patel Y, Offer G, Marinescu Met al., 2022, Thermal evaluation of lithium-ion batteries: Defining the cylindrical cell cooling coefficient, Journal of Energy Storage, Vol: 54, Pages: 1-9, ISSN: 2352-152X

Managing temperatures of lithium-ion cells in battery packs is crucial to ensuring their safe operation. However, thermal information provided on typical cell datasheets is insufficient to identify which cells can be easily thermally managed. The Cell Cooling Coefficient (CCC) aims to fill this gap, as a metric that defines the thermal dissipation from a cell when rejecting its own heat. While the CCC has been defined and used for pouch cells, no similar measure has been proven for cylindrical cells. This work successfully defines and measures the CCC for cylindrical cells under base cooling (CCCBase), defined as the heat rejected through the base divided by the temperature difference from the base to positive cap. Using a non-standard, electrically optimised connection, the maxima for CCCBase of an LG M50T (21700) and Samsung 30Q (18650) cell are successfully measured to be 0.139 and 0.115 W K−1, respectively. Even though the 21700 has a higher CCCBase, indicating that the cell can be cooled more efficiently, comparing the CCCBase per area the 18650 can reject 13 % more heat for a given cooled area. A worked example demonstrates the equal importance of understanding heat generation alongside the CCC, for both cell design and down selecting cells.

Journal article

Diaz LB, Hales A, Marzook MW, Patel Y, Offer Get al., 2022, Measuring Irreversible Heat Generation in Lithium-Ion Batteries: An Experimental Methodology, JOURNAL OF THE ELECTROCHEMICAL SOCIETY, Vol: 169, ISSN: 0013-4651

Journal article

Edge JS, O'Kane S, Prosser R, Kirkaldy ND, Patel AN, Hales A, Ghosh A, Ai W, Chen J, Yang J, Li S, Pang M-C, Bravo Diaz L, Tomaszewska A, Marzook MW, Radhakrishnan KN, Wang H, Patel Y, Wu B, Offer GJet al., 2021, Lithium ion battery degradation: what you need to know, Physical Chemistry Chemical Physics, Vol: 23, Pages: 8200-8221, ISSN: 1463-9076

The expansion of lithium-ion batteries from consumer electronics to larger-scale transport and energy storage applications has made understanding the many mechanisms responsible for battery degradation increasingly important. The literature in this complex topic has grown considerably; this perspective aims to distil current knowledge into a succinct form, as a reference and a guide to understanding battery degradation. Unlike other reviews, this work emphasises the coupling between the different mechanisms and the different physical and chemical approaches used to trigger, identify and monitor various mechanisms, as well as the various computational models that attempt to simulate these interactions. Degradation is separated into three levels: the actual mechanisms themselves, the observable consequences at cell level called modes and the operational effects such as capacity or power fade. Five principal and thirteen secondary mechanisms were found that are generally considered to be the cause of degradation during normal operation, which all give rise to five observable modes. A flowchart illustrates the different feedback loops that couple the various forms of degradation, whilst a table is presented to highlight the experimental conditions that are most likely to trigger specific degradation mechanisms. Together, they provide a powerful guide to designing experiments or models for investigating battery degradation.

Journal article

Offer G, Patel Y, Hales A, Bravo Diaz L, Marzook Met al., 2020, Cool metric for lithium-ion batteries could spur progress, Nature, Vol: 582, Pages: 485-487, ISSN: 0028-0836

Journal article

O'Kane SEJ, Campbell ID, Marzook MWJ, Offer GJ, Marinescu Met al., 2020, Physical origin of the differential voltage minimum associated with lithium plating in Li-Ion batteries, Journal of The Electrochemical Society, Vol: 167, Pages: 1-11, ISSN: 0013-4651

The main barrier to fast charging of Li-ion batteries at low temperatures is the risk of short-circuiting due to lithium plating. In-situ detection of Li plating is highly sought after in order to develop fast charging strategies that avoid plating. It is widely believed that Li plating after a single fast charge can be detected and quantified by using a minimum in the differential voltage (DV) signal during the subsequent discharge, which indicates how much lithium has been stripped. In this work, a pseudo-2D physics-based model is used to investigate the effect on Li plating and stripping of concentration-dependent diffusion coefficients in the active electrode materials. A new modelling protocol is also proposed, in order to distinguish the effects of fast charging, slow charging and Li plating/stripping. The model predicts that the DV minimum associated with Li stripping is in fact a shifted and more abrupt version of a minimum caused by the stage II-stage III transition in the graphite negative electrode. Therefore, the minimum cannot be used to quantify stripping. Using concentration-dependent diffusion coefficients yields qualitatively different results to previous work. This knowledge casts doubt on the utility of DV analysis for detecting Li plating.

Journal article

Hales A, Marzook MW, Bravo Diaz L, Patel Y, Offer Get al., 2020, The surface cell cooling coefficient: a standard to define heat rejection from lithium ion battery pouch cells, Journal of The Electrochemical Society, Vol: 167, ISSN: 0013-4651

There is no universal and quantifiable standard to compare a given cell model's capability to reject heat. The consequence of this is suboptimal cell designs because cell manufacturers do not have a metric to optimise. The Cell Cooling Coefficient for pouch cell tab cooling (CCC tabs ) defines a cell's capability to reject heat from its tabs. However, surface cooling remains the thermal management approach of choice for automotive and other high-power applications. This study introduces a surface Cell Cooling Coefficient, CCC surf which is shown to be a fundamental property of a lithium-ion cell. CCC surf is found to be considerably larger than CCC tabs , and this is a trend anticipated for every pouch cell currently commercially available. However, surface cooling induces layer-to-layer nonuniformity which is strongly linked to reduced cell performance and reduced cell lifetime. Thus, the Cell Cooling Coefficient enables quantitative comparison of each cooling method. Further, a method is presented for using the Cell Cooling Coefficients to inform the optimal design of a battery pack thermal management system. In this manner, implementation of the Cell Cooling Coefficient can transform the industry, by minimising the requirement for computationally expensive modelling or time consuming experiments in the early stages of battery-pack design.

Journal article

Hales A, Diaz LB, Marzook MW, Zhao Y, Patel Y, Offer Get al., 2019, The cell cooling coefficient: A standard to define heatrejection from lithium-ion batteries, Journal of The Electrochemical Society, Vol: 166, Pages: A2383-A2395, ISSN: 0013-4651

Lithium-ion battery development is conventionally driven by energy and power density targets, yet the performance of a lithium-ion battery pack is often restricted by its heat rejection capabilities. It is therefore common to observe elevated cell temperatures and large internal thermal gradients which, given that impedance is a function of temperature, induce large current inhomogeneities and accelerate cell-level degradation. Battery thermal performance must be better quantified to resolve this limitation, but anisotropic thermal conductivity and uneven internal heat generation rates render conventional heat rejection measures, such as the Biot number, unsuitable. The Cell Cooling Coefficient (CCC) is introduced as a new metric which quantifies the rate of heat rejection. The CCC (units W.K−1) is constant for a given cell and thermal management method and is therefore ideal for comparing the thermal performance of different cell designs and form factors. By enhancing knowledge of pack-wide heat rejection, uptake of the CCC will also reduce the risk of thermal runaway. The CCC is presented as an essential tool to inform the cell down-selection process in the initial design phases, based solely on their thermal bottlenecks. This simple methodology has the potential to revolutionise the lithium-ion battery industry.

Journal article

Campbell ID, Marzook M, Marinescu M, Offer GJet al., 2019, How observable Is lithium plating? Differential voltage analysis to identify and quantify lithium plating following fast charging of cold lithium-Ion batteries, Journal of The Electrochemical Society, Vol: 166, Pages: A725-A739, ISSN: 0013-4651

Fast charging of batteries is currently limited, particularly at low temperatures, due to difficulties in understanding lithium plating. Accurate, online quantification of lithium plating increases safety, enables charging at speeds closer to the electrochemical limit and accelerates charge profile development. This work uses different cell cooling strategies to expose how voltage plateaus arising from cell self-heating and concentration gradients during fast charging can falsely indicate plating, contrary to prevalent current assumptions. A solution is provided using Differential Voltage (DV) analysis, which confirms that lithium stripping is observable. However, scanning electron microscopy and energy-dispersive X-ray analysis are used to demonstrate the inability of the plateau technique to detect plating under certain conditions. The work highlights error in conventional plating quantification that leads to the dangerous underestimation of plated amounts. A novel method of using voltage plateau end-point gradients is proposed to extend the sensitivity of the technique, enabling measurement of lower levels of lithium stripping and plating. The results are especially relevant to automotive OEMs and engineers wishing to expand their online and offline tools for fast charging algorithm development, charge management and state-of-health diagnostics.

Journal article

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