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...
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.
Lithium-ion batteries get hot, and it is hard to keep them cool. Industry has paid too little attention to this problem for the past decade. The focus has been elsewhere: on cutting costs and on boosting the amount of energy a single cell in a battery can store (energy density). This strategy has, for example, increased the longevity and capabilities of mobile phones. Future applications, such as electric vehicles and smart grids, need thousands of cells in a battery pack. These are prone to overheating.Manufacturers of large, high-energy battery packs must design complicated systems to manage heat. The battery pack in electric-vehicle maker Tesla's Model 3 car, for example, holds more energy than 6,000 iPhone 11 handsets. Coolant fluid is pumped through a network of channels to carry heat away from the individual cells. But these cumbersome additions make the battery pack heavy and drain its energy 1 . Developers are wasting time and money on these inefficient designs. Heat-removal strategies must be improved to make battery packs both light and powerful.Why this lack of attention? One reason is that there is no standard way of judging the thermal performance of battery packs. Manufacturers of single cells compete by chasing ever greater energy density. Their product-specification sheets do not cover how easy it is to remove heat from a cell. Designers of battery packs A new measure for the rate of heat removal from battery packs gives manufacturers a simple way to compare products.
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
) 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
which is shown to be a fundamental property of a lithium-ion cell. CCC
is found to be considerably larger than CCC
, 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.
To realise the promise of solid-state batteries, negative electrode materials exhibiting large volumetric expansions, such as Li and Si, must be used. These volume changes cause significant mechanical stresses and strains that affect cell performance and durability; however their role and nature are poorly understood. Here, a 2D electro-chemo-mechanical model is constructed and experimentally validated using steady-state, transient and pulsed electrochemical methods. The model geometry is a representative cross-section of a non-porous, thin-film solid-state battery with an amorphous Si negative electrode, LiPON solid electrolyte and LiCoO2 positive electrode. A viscoplastic model is used to predict the build-up of strains and plastic deformation of Si as a result of (de)lithiation during cycling. Electrochemical impedance spectroscopy, the galvanostatic intermittent titration technique and hybrid pulse power characterisation are carried out to establish key parameters for model validation. The validated model is used to explore the peak interfacial stress and strain as a function of the relative electrode thickness (up to a factor of 4), revealing a peak volumetric expansion from 69% to 104% during cycling at 1C. The validation of this electro-chemo-mechanical model under load and pulsed operating conditions will aid in the cell design and optimisation of solid-state battery technologies.
Power consumption from electrical devices increases year upon year, and as a result thermal management of power electronics is becoming ever more relevant. This review summarises the advancements made in the piezoelectric fan optimisation since their invention in the late 1970s. Energy consumption is highly relevant, and is an underlying theme throughout. Emphasis is placed on the methods undertaken to optimise designs for many different applications, and critical analysis of these processes is included. Comparison of data taken from different studies highlights the well-established rules of piezoelectric fan design and, more importantly for future advancements, also identifies the aspects of design which are not fully understood. Numerical modelling has become an
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