Effect of coating operating parameters on electrode physical characteristics and final electrochemical performance of lithium-ion batteries

Abstract

The effect of coating parameters of NMC622 cathodes and graphite anodes on their physical structure and half-cell electrochemical performance is evaluated by design of experiments. Coating parameters include the coater comma bar gap, coating ratio and web speed. The electrochemical properties studied are gravimetric and volumetric capacity, rate performance, areal specific impedance (ASI) and C-rate. Differences in the manufacturing effects on the electrode physical structure and electrochemical performance are observed between the electrodes and are modelled by linear regression. The effect of cell coating weight and porosity on half-coin cell electrochemical performance is also evaluated by linear regression. The cathode performance at high gravimetric and volumetric C-rates is mainly influenced by coating weight, whereas porosity is the only explanatory variable for volumetric C-rates of 1C and below. For anode, correlations are only found for the C/20 and 5C gravimetric and volumetric capacities and are related to coating weight. An inverse relationship between ASI and coating weight is observed for cathode, but in general the cell physical characteristics cannot completely explain the observed ASI for both electrodes. The obtained models are useful for the design and robust manufacturing of electrodes since present a quantitative relationship between the coating parameters, cell characteristics and final cell electrochemical performance.

Measurement of anisotropic volumetric resistivity in lithium ion electrodes

“…40 One part of the Nextrode project is using a Design of Experiments (DoE) approach to investigate electrode manufacturing. 41,42 The most recent DoE has looked at the formulation of cathode mixes, with LFP as the active material. 43,44 The previous DoE investigated different calendering pressures and temperatures on graphite anodes and NMC-622 cathodes, prepared at different coat weights.…”

Impact of Formulation and Slurry Properties on Lithium‐ion Electrode Manufacturing

“…The systematic and model-based manufacturing for rechargeable energy storage devices and particularly lithium-ion batteries has been a new topic to the field. The data driven models for capturing the dependency of the mixing, [7] coating process, [8,9] calendering, [10][11][12] drying [13,14] and electrolyte injection [15] are shown to perform well in laboratory and pilot scale manufacturing. These studies try to quantify the effect of some of the critical decision factors, such as coating speed, coating gap, calendering pressure, calendering roll temperature, drying air speed and temperature, on the responses (such as coating porosity, coating thickness) at the end of each step and investigate that further towards the cell characterisations 9such as capacity, internal resistance).…”

Performance Evaluation of Convolutional Auto Encoders for the Reconstruction of Li-Ion Battery Electrode Microstructure

“…A comprehensive understanding of the relationship between the characteristics of the electrodes (cathode and anode) and the cells' electrochemical performance over a complete range of load-cycles and environmental conditions is necessary for a successful design but very hard to achieve [3]. This is due to the large number of electrode-related factors and control variables that have strong interdependencies with each other and with the performance indices of the cells [4][5][6][7][8]. The electrode characteristics at the microstructure level are the most decisive for the cell performance [9], and stability [10], where the microstructure here is referring to stochastic geometrical characteristics at the micrometre and sub-micrometre scales [11].…”