With the advancement of IoT and 5G communications, the need for EMC solutions to maintain signal integrity and prevent electromagnetic interference is growing day by day. The demand for EMI filtering solutions is expected to increase in the automotive, medical, military, and home appliance industries to reduce EMI.

According to global market research firm Markets and Markets, the EMI/EMC filter market is expected to grow at a compound annual growth rate of 5% from USD 1.24 billion in 2024 to USD 1.58 billion (KRW 2.2 trillion) in 2029.

The EMI/EMC filter market has grown in tandem with the increase in adoption of electric vehicles. Electronic components that make up electric vehicles, such as battery management systems (BMS), inverters, electric motors, and electronic control units, are vulnerable to electromagnetic interference, and malfunctions can lead to major functional safety issues.

Accordingly, international standards and manufacturers are demanding high functional safety and strict regulations, influencing the adoption of advanced EMI/EMC filter technologies.

Additionally, the expansion into 5G and 6G communications leads to the importance of EMI management due to increased communication density and proximity. EMI/EMC filters contribute to maintaining 5G integrity and stability by preventing issues such as signal degradation or data loss, and focus on providing seamless connectivity by blocking unwanted frequency/electromagnetic signals.

In particular, the EMI/EMC filter market appears to be attempting to combine generative AI and AI technologies to cope with the increasingly complex radio environment. The report stated that “integrating generative AI and AI with EMC filtering can have a revolutionary impact on design and operational efficiency.”

AI can help analyze complex systems and predict interference behavior, predict EMI problems, and reduce prototyping time and costs. AI can also be used for real-time monitoring and improved adaptive filtering.

In fact, Ulsan National Institute of Science and Technology has studied deep learning-based algorithms to remove electromagnetic interference noise in photoacoustic endoscope image processing and confirmed the possibility of application in the medical field, and the iSIS Institute for Smart and Security Systems at the University of Applied Sciences and Arts Western Switzerland has studied EMI automatic filtering using neural networks and applied this to a smart inductive proximity sensor, successfully reducing noise by 70% with a 2KB memory-level recurrent neural network (RNN).

In addition, the Department of Electrical and Electronic Engineering at the University of Hong Kong conducted and announced research on eliminating EMI in MRI environments with no or incomplete RF shielding through EMI removal using active sensing and deep learning prediction. The Department of Electrical Engineering at Zhejiang University in China also conducted research on modeling and optimization of EMI filters using artificial neural networks.

“Machine learning algorithms are expected to enable improved performance in variable electromagnetic noise environments, with signal analysis and dynamic adjustment of filter parameters,” the Markets and Markets report said. “Furthermore, AI-enhanced diagnostics enable more accurate error detection in EMC filters, contributing to equipment life and stability,” it added.

In a previous EMI/EMC Expert Talk interview, Dr. Lee Jun-sang said, “AI-based simulation tools will be able to agilely ensure EMI/EMC compliance and reliability by monitoring real-time EMI/EMC performance and providing component optimization strategies when components are changed in the BOM.” He added, “AI will streamline the EMI/EMC compliance process, accelerate the design cycle, and drive innovation in the electronics manufacturing industry.”

Following the DeepSearch issue, cheap and efficient reinforcement learning-based AI modeling is rapidly emerging as a new trend, and as AI technology innovation continues to lead the industry and academia, it is anticipated that the future trend will have a ripple effect on the EMI/EMC field.