EV Battery Production

The battery manufacturing industry is forecast to be one of the fastest growing production industries in the next decade, with annual global lithium-ion battery capacity demand expected to increase from 160 GWh cell energy in 2018 to > 1000 GWh cell energy in 2030, triggering expected investments of more than $100 billion and generating annual revenue of more than $100 billion [1]. To transform these investments into sustainable business models, cost efficient battery manufacturing is a prerequisite to make EVs competitive compared to internal combustion engine vehicles. The same applies to other industries and products requiring lithium-ion batteries.

An important challenge in battery production is optimisation of the manufacturing process to improve long-term cycling performance and capacity lifetime whilst reducing and controlling manufacturing costs. A key step in production, which determines the final quality of the battery pack, is the manufacturing process for the electrodes, with emphasis on the quality and consistency of the coatings used on both cathodes and anodes. Electrodes are manufactured by coating the current collectors, which are typically aluminium for cathodes and copper for anodes.

The coatings are a slurry mixture comprised of active materials, e.g. Lithium- Nickel-Magnesium-Cobalt-Oxide (NMC) in a typical lithium-ion cathode and graphite for an anode. The coating also typically includes conductive carbon nanoparticles (e.g. carbon black), a polymer binder and a solvent. This mixture is then dried by exposure to airflow, heat, a reduction in ambient pressure, radiation or other more advanced drying processes [2]. A calendar process is then used to compress the dry coatings to increase the energy density of the cell via reduction in porosity, but leaving sufficient porosity for lithium transport and other forms of conduction [3].

There are a number of key performance indicators in the electrode production process that allow the homogeneity, quality and performance of the cathode and anode coatings to be continually optimised, monitored and maintained.

• Density of the coating – important towards maximising the energy density of the battery cell but leaving sufficient porosity for lithium transport and other conduction mechanisms. The mass of active material per unit area dictates the final capacity of the electrode and while higher coat weights are desirable to increase energy density, they typically also lower the power density. Hence, there needs to be a compromise between the two, giving the maximum energy density while satisfying the power requirements needed for the application. For this reason, specific control of the coating density is highly desirable. Density is thus a key variable in dictating electrochemical properties of coatings.
• Thickness of the coating – ensuring the homogeneity of coating thickness in the production process and final product. Thicker electrodes contain a greater amount of active materials, increasing energy density, but also have greater diffusion distances, lowering power output, as well as potentially causing uneven response across the electrode and leading to quicker degradation. Hence, there exists an optimum thickness to balance these effects, and control over the thickness is important [2].
• Conductivity of the coating - high conductivity improves the capacity at higher discharge rates, with more energy extracted from the battery at a given time [4].

There are a variety of different stages of the production process where it would be extremely beneficial to measure these key performance indicators.

• Before or after the coating drying process when the coating has been applied to the current collector metal substrates. The coating and drying process alone are currently reported to make up 22% of the total cost of electrode manufacture [2].
• Before or after the calendaring process when the dry coating is compacted.

Currently, losses in the manufacturing of lithium-ion batteries due to scrappage of out-of-specification electrodes can runs as high as 2-5% of output [5,6], with even higher numbers possible at the ramp-up of new manufacturing runs. This wastage contributes overall battery cost, and becomes very significant as production is scaled up in giga factories.

The ability to rapidly monitor coating thickness, density and conductivity in the production of electrode coatings and provide real-time feedback for process control is an important contributor towards eliminating wastage costs and ensuring supply to market without production stoppage.

The manufacturing process for lithium-ion electrodes is a developed field with different techniques for monitoring processes. However, these techniques do not provide all of the key performance indicators noted above, are often used in isolation and tend to be used off-line as quality control measures. Off-line techniques such as sampling and weighing a coated electrode vs. uncoated substrate are also used. However, on large scale production, the off-line trial-and-error approach can lead to much additional wastage and equipment downtime [2]. In-line techniques measure more of the coating than taking sample points and often offer improved detection of faults in the coating through more extensive inspection. Rapid in-line measurements also offer the opportunity for real-time process control as noted above, with cost reduction and insurance-of-supply benefits.

There is currently no technology that can measure coating density, thickness and conductivity in-line directly and simultaneously. For example, laser triangulation or laser callipers at near infrared wavelengths can be used [2] to estimate thickness but are difficult to implement with opaque coatings and frequently require calibration to uncoated substrates as well as maintaining precise alignment in production environments, which leads to inaccuracies. Sensors are available to measure coating weight. X-Ray, beta and gamma radiation can be used in transmission and reflection geometries but suffer from both safety concerns as well as the need (in the case of beta sensors) to integrate over long timescales to collect accurate signals. For the high coating speeds used in industry, this can cause significant areas of the coating to be missed. Ultrasound can also be used to measure the weight of coated material but relies on stable and accurate calibrations.

Moreover, in all of the above, the coating weight is measured and not the coating density which is the desired performance indicator. Coating density can be calculated and thus indirectly estimated but relies on measurements of thickness from yet another set of sensors, introducing further errors. The optimum configuration would be a single sensor for both in-line thickness and coating density measurements. This sensor would allow in-line control by feeding back the coating thickness and density in real-time into the coating deposition control process (e.g. modifying the speed of the production line, gaps used in deposition system, etc.) to optimise coating and maintain quality. Thus far, this in-line process has not proven possible with the measurement technologies mentioned above.

Terahertz pulsed technology, operating between microwaves and infrared, offers a solution; a single sensor that measures all three key performance – coating density, thickness and conductivity. Over the last decade, Terahertz has become an established inspection tool in process control and production in a variety of industries including advanced semiconductor packaging [7], automotive paint thickness measurements on car production lines [8] as well as in-line coating thickness measurements on automotive parts. The Terahertz technique uses highly accurate time of flight measurements (Figure 1) to determine coating thickness based on multiple reflections of Terahertz pulses from different coating interfaces. The technique operates as a high frequency pulsed radar system, where time of flight is converted into coating thickness.

Figure 1: Coating thickness determined from Terahertz pulse measurements.

An additional and substantial advantage of Terahertz over other techniques is its ability to simultaneously measure the real (n_o) and imaginary (k) parts of the refractive index of the coating, n = n_o+ik. This unique capability of Terahertz pulses provides important information on key performance indicators for the coating.

• Thickness of the coating: Coating thickness d can be calculated using the formula d = cΔt/2n where c is the speed of light, n is the index of refraction and ∆t is the time delay of the Terahertz pulse from the coating interface; see Figure 1.
• Density of the coating: The real part of the index of refraction n_o of a material in the Terahertz is proportional to the bulk density of the material [9] and can be used to directly measure the density with the aid of calibration; see Figure 2.
• Conductivity of the coating: The imaginary part of the index of refraction k of a material in the Terahertz is related to its high frequency conductivity σ using the equation σ(ω) = n_ockω, where ω is the Terahertz frequency, enabling the electrical properties of the film to be monitored and adjusted during the production process, or to be used off-line in the modelling and prediction of the process.

Figure 2: Effect of density of material on Terahertz refractive index [9].

TeraView has used its proprietary Terahertz pulsed technology to measure coatings in a variety of different applications. Working with leading automotive lithium-ion battery manufacturers as well as academic collaborators, TeraView is extending these capabilities to coatings on battery electrodes. In collaboration with the Faraday Institute and the University of Birmingham in the UK, TeraView has measured coated films on cathodes and anodes, summarized in Figure 3 and Figure 4 below.

Figure 3 shows a Terahertz measurement of cathodes based on NMC (Lithium-Nickel-Manganese-Cobalt-Oxide) on aluminium. To illustrate the wide range of the Terahertz measurement, both thin (15μm) and thick coatings (70μm) were investigated. The twin peaks in the Terahertz waveforms are shown to illustrate the ease with which the front and rear interfaces of the coating are resolved and coating thickness correctly measured. In a production system a simple value of coating thickness is automatically returned to the operator or plant data management system. A scan of the Terahertz sensor across the width of the cathode reveals the surface and sub-surface coating profiles, as well as a linear plot of coating thickness itself across the cathode; see Figure 3c below.

Figure 3: Cathode - Terahertz measurements of NMC coating on aluminium: (a) thin coating, (b) thick coating and (c) cross sectional image of coating thickness across the cathode, demonstrating the ability of Terahertz to measure and map thickness across cathodes used in lithium-ion batteries.

Figure 4 shows a Terahertz measurement of an anode coating based on graphite mixed with carbon black and binder on copper. Graphite is more absorbing in the Terahertz, but two peaks in the Terahertz waveforms are nevertheless resolved, identifying the front and rear interfaces of the coating and correctly returning the coating thickness. The measurement has also been demonstrated on thicker anode coatings, and builds on TeraView years of experience measuring graphite layers in other coating production applications.

Figure 4: Anode - Terahertz measurements of graphite coating on copper: (a) waveform showing reflections from surface and back of coating and yielding thickness of 60mm (b) distribution of layer thickness across a 8mmx8mm portion of anode film.

TeraView’s products have an established track record in production applications across a range of industries where coating measurements are key to process quality and control, and where maintaining supply of product is essential.

Figure 5: TeraCota coating measurement system in production: (a) TeraCota core system, (b) TeraCota sensor provided for remote access on umbilical, (c) production application at US automotive facility showing system, sensor and automation (robotic) platform and (d) TeraCota sensor used in dusty industrial environment.

TeraView’s TeraCota product (Figures 5a & 5b) has been deployed in automotive production plants in Europe, the US and Asia to measure coatings. By way of example, a deployment at a large US facility is shown in Figure 5c. These installations have involved addressing a host of issues associated with production environments including vibration, temperature changes etc. Reproducibility and accuracy of data has been extensively demonstrated. TeraView’s sensor heads have also been designed to be used in dusty environments (e.g. Figure 5d).

There are a number of stages in the production process of both cathodes and anodes where Terahertz sensors could play a role in process control and reducing wastage; see figure Figure 6 below. An optimum in-line configuration would measure coating thickness and density, and feedback these parameters to control the coating speed and gap. There is additional value in making these measurements both before and after drying. Comparing the wet thickness to the applied gap will give information about the elasticity in the process.

The dry coating density and thickness, measured by Terahertz, will dictate the energy and power capacity of the coating and so will be the ultimate factors to optimise by changing the gap and speed of coating production. TeraView’s unique solution to measuring thickness, density and conductivity simultaneously and in real-time allows for feedback and control of these production parameters, tailored to meet customer requirements.

Figure 6: Key stages and parameters in the production of electrode coatings, and feedback control of production using coating thickness and density measured by terahertz sensors at different parts of the process. [3].

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4. https://undergraduateresearch.virginia.edu/investigating-conductivity-lithium-ion-batteries-across-porous-thin-films-through-manipulation-0.
5. Journal of Minerals, Materials and Metals 69 (2017) 1484– 1496.
6. Int. J. Prod. Econ. 232 (2021) 107982.
7. ‘Localization and Characterization of Defects for Advanced Packaging Using Novel EOTPR Probing Approach and Simulation‘, NVIDIA Corporation, Proceedings of the ISTFA Conference 2020 (2020).
8. ‘Use of Terahertz-Based Sensing to Quantify Layer Thickness in Automotive Paint Systems ‘, M Nichols & T Misovski, Ford Motor Company, Proceedings of the SAE Conference April 2022 (2022).
9. Journal of Pharmaceutical Sciences On-line DOI 10.1002/jps.23560 (2013).