Intelligent laser welding with dynamic beam shaping function can reduce the demand for filler wire

In EU project ALBATROSS, Fraunhofer IWS has developed battery housing for E-vehicles.

Laser processes with dynamic beam shaping create stable joints even in challenging material combinations. Recent applications demonstrate how to eliminate filler materials while improving quality, energy efficiency, and production logic.
Fraunhofer Institute for Material and Beam Technology (IWS) will present novel laser welding solutions at the trade fair Schweißen & Schneiden 2025 (Joining-Cutting-Surfacing) in Essen, Germany, between 15-19 September.

Stable laser welding method for aluminum die castings and extruded profiles

The focus of the newly-developed processes is on intelligently-guided beam processes that operate without filler wire and can be transferred into real production scenarios. Industries already applying the technology include lightweight structures for e-mobility, aerospace tanks, and load-bearing components in steel construction.

Several current development projects rely on laser-based joining. A precisely controlled beam actively influences melt behavior, eliminating the need for filler wire. “We demonstrate that even the most demanding welding tasks – such as joining of difficult-to-weld material alloys or welding of heavy sections – can be performed robustly and productively with less energy, material, and rework,” said Dr. Axel Jahn, Head of the Joining Department at IWS.

Aluminum battery housing

In the EU project ALBATROSS, IWS developed an innovative laser-fabricated battery housing for electric vehicles and successfully demonstrated it at full component scale. The lightweight design combines aluminum extrusion profiles with die-cast aluminum parts, featuring walls up to 5 mm in thickness.

“Our solution relies on targeted oscillation of the laser beam, which moves the melt pool, reduces pores, and produces metallurgically stable welds,” said Jahn. “This allows us to generate high-quality aluminum welds without the filler material usually required.”
The housing has already been integrated and tested in a real vehicle model. Within the Fraunhofer lead project FutureCarProduction, the technology is now being advanced for secondary aluminum and cast-to-cast joints, alongside a sustainability assessment.

For aerospace applications, Fraunhofer IWS has developed a laser welding process with dynamic beam shaping to produce closed tank structures from high-strength 2000-series aluminum alloys. The new laser process operates without filler material and achieves stable, low-heat welding even on three-dimensional contours. “The process is ideal for closing rotationally symmetric containers and is also under study for pipe welding,” Jahn said.

Laser-welded aluminum battery housing

…and Fraunhofer IOSB system monitors movements in cars

The Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB) has developed an intelligent vision technology that uses AI to automatically log and analyze human movements inside vehicles. Called the AktiMeter, the system is suited to market research, user-centered product development and ergonomic studies, says IOSB.

Eye tracking systems are already in use in many industries, such as market research and development of distraction-free vehicle features. The AktiMeter captures information on vehicle occupants’ entire bodies. This provides insight into people’s sitting positions, movements and gestures, activities and intentions.

The technology can determine where a person’s arms and hands are located, in which direction the driver’s head turns and what objects are used in the vehicle’s interior. This opens up new prospects for research, as long car trips can be analyzed automatically.
IOSB specializes in computer vision, which means the researchers there interpret anything and everything that can be captured by optical sensors. Frederik Diederichs and his team use this information to improve human-AI interactions inside the vehicle. Future self-driving applications could benefit from the data collected, as it serves as a basis for developing smart driver assistance systems that respond to the behavior and needs of vehicle occupants.

AktiMeter suits market research, product development and ergonomic studies

AI and machine learning

The AktiMeter combines computer vision techniques based on AI, which can recognize body poses and objects, with a 3D model of the vehicle. Machine learning processes can then draw further conclusions from this, for example about the activity. This approach is especially suitable for fast, energy-conserving analyses without a cloud connection or powerful hardware in the car itself.

Automatic data interpretation is used to create a 3D digital twin of the vehicle’s interior. This data source is used to draw conclusions directly in the vehicle. This minimizes the amount of storage required while eliminating the need to store image data that could pose issues under the EU General Data Protection Regulation (GDPR).

“Previous [analytical] methods are trained on predefined situations from which training data was collected in a laborious and time-consuming process. Thanks to the use of generative AI, it is now possible to use the AktiMeter to define situations flexibly without having to collect training data,” said Manuel Martin, a senior scientist in the Perceptual User Interfaces working group at IOSB.

The researchers will be presenting their technology in a level 3 automated vehicle at the joint Fraunhofer booth at IAA MOBILITY, between September 9–12, in Munich, Germany.

Source: optics.org