Ensuring the Quality of EV Batteries with CT-Scan Data Analysis and Visualization

Being able to check, detect, and correct errors in batteries early on decreases the potential for failure throughout a battery’s lifetime.

April 1, 2025

In the current, fluctuating state of global demand for EVs, market growth has slowed — yet still remains positive. Moving forward in time, the shift to a greater percentage of EVs worldwide appears inevitable. As a result, competition will only get fiercer: Manufacturers and automotive OEMs alike must match the pace of production to market realities, price accurately, and meet consumer expectations of reliability, to survive.

Research and development aimed at optimizing both the technology and the cost of that most expensive of EV components — the battery — continues apace. Not only are the makers of current batteries under pressure to produce the highest-quality product, but they may also be considering how to participate and compete in the next-generations of these key components.

While striving for optimal economics, battery manufacturers must, above all, deliver quality. To address the core issue of EV battery quality, CT scanning and subsequent data analysis, at several stages of production, is becoming increasingly valuable. Waiting to test quality until a battery comes off the line, or is about to be installed in a vehicle, can be incredibly inefficient and expensive; the only way to see inside a finished battery is to open it up — which destroys it.

Two views of battery anode overhang analysis. Left shows the anode overhang in a 2D slice where the anodes are coded by color with respect to their corresponding anode overhang. Right is a 3D representation of the jellyroll to get an overview over the dataset, e.g., to judge the segmentation quality. (Image: Volume Graphics/Hexagon)

Deeper Insights

While X-ray, ultrasonic testing for electrolytes, and visual checks can serve certain applications, industrial CT scan-data analysis provides deeper, more holistic insights that inform every discipline in the battery creation stream. These include R&D, design, simulation, assembly-stage inspection, final production inspection, and forensic/root-cause analysis used to understand accidents and failures as well as to certify used batteries.

Delamination in a wound battery. (Image: Waygate Technologies)

Being able to check, detect, and correct errors in batteries early on, such as contamination by particulate matter, improper anode overhang, or hazardous pores in the housing weld seam, decreases the potential for failure throughout a battery’s lifetime. Potency and output can be negatively affected by the thickness of anodes and cathodes, the behaviour of the active material on a micro level, temperature imbalance and more.

By comprehensively characterizing the structure of active material on the nanoscale, developers can gain profound insights into lithium-ion (Li-ion) flow, and other factors, which can be incorporated into competitive, successful designs. This is equally true for newer, Li-ion battery alternatives such as solid-state approaches.

Here are some examples of battery-related quality issues that can be detected and categorized using CT-scan data analysis and visualization, thereby improving yields and scalability.

Controlling and Optimizing Overhand

CT scanning captures 3D images of battery components at critical production stages, for early detection of defects that arise during stacking, assembly, welding, and/or filling. Advanced inspection software processes this image data into holistic, accurate visualizations and analyses of any anomalies. In addition, it can provide critical feedback for designers and engineers to incorporate as they model, refine, and optimize geometries, materials, and processes. This saves valuable time, resources, and ensures that the final product is of the highest-possible quality. (Image: Volume Graphics/Hexagon)

The anode overhang in Li-ion batteries is a crucial safety criterion. Advanced CTbased inspection software helps manufacturers and researchers measure and design anode overhangs that balance electrode utilization, current distribution, cycling stability, and safety considerations. Carefully controlling and optimizing the overhang improves the efficiency, capacity, stability, and overall performance of batteries.

Analysis of particles in the jellyroll of a battery in VGSTUDIO MAX. The software classifies the shapes and sizes of these tiny, foreign inclusions and based on customized criteria, calls them out by highlighting them in colors that indicate size. (Image: Waygate Technologies)

Any time the active material in a battery becomes separated from the current collector, be it during manufacturing or over time, electrical output starts to become affected. Ripples in the metal sheeting can develop — this is more an issue with wound batteries than stacked ones — creating undulations that can affect anode and cathode alignment, impacting performance and lifespan. Inspection software can detect and visualize such delamination not only during manufacturing, but also in later maintenance if delamination occurs after multiple charging cycles.

Detecting Unwanted Particles

Foreign particles can make their way into a battery at several stages of production. Porosity inclusion analysis allows engineers to detect these in the CT-scan data and quantify their size and location to help determine whether they are critical or not.

Unwanted particles can be a side-effect of welding, resulting from flying hot metal as it cools. Particles can also occur when anodes and/or cathodes are cut from sheets of aluminium or copper. When flakes show up on a CT scan analysis, the software calls out their irregular shapes and anomalies to support decisions about potential battery quality.

Porosity Inclusion Analysis

Porosity detection in the weld seam of a battery; the size of individual pores is indicated by color. (Image: Volume Graphics/Hexagon)

Weld-seam porosity arising from when battery-casing components are welded together is almost impossible to avoid completely. But it can be reduced through post-analysis weld-parameter optimization.

Porosity inclusion analysis software helps quality engineers decide whether a particular pore is a reason for concern. By leveraging this analysis, manufacturers can ensure the integrity and optimal performance of their batteries.

Application to Serial Production

It is crucial to identify any potential battery defects and make various measurements during key production phases. Inline measurements, captured via CT scans, should ideally be made at every critical stage of the battery-making process. This provides the level of quality assurance that will prevent accelerated degradation, preserve battery lifespan throughout the operating lifecycle, and improve a manufacturer’s product quality and competitive edge as the future of EVs evolves.

This article was written by Kai Winter, Business Enablement Manager, Hexagon Manufacturing Intelligence (Stockholm, Sweden). For more information, visit here .