Electrical arcs are one of the most dangerous and costly failure modes in modern power systems. From solar inverters and battery storage to AI data center power distribution unit (PDU) and direct current (DC) fast chargers, the market is urgently shifting towards real-time arc fault detection, delivered at the edge, with high reliability and low power.
An Arc Fault Circuit Interrupter (AFCI) matters more than ever because arc faults can ignite fires, damage equipment, and result in significant downtime. Traditional protection methods struggle with:
- High-frequency noise
- Wide operating currents
- Complex loads
- Evolving environmental conditions
Renesas supports AFCI implementations with two hardware approaches that provide design flexibility, configurability, and robust detection accuracy. With the combination of mixed-signal configurability + MCU intelligence + Edge AI inference, Renesas can transform legacy solutions to maximize the design choices and ensure reliability.
Real-Time AI for Arc Detection Based on MCU Intelligence
Real-time Analytics for arc detection enhances safety, reduces false alarms, and enables proactive maintenance in electrical systems. This is made possible with the RA6M3/RA6M4 MCUs powered by an Arm® Cortex®-M33 processor with up to 200MHz and DSP-rich architectures. AI inference is made possible by connecting to the Real-Time Analytics (RTA) models generated by Reality AI Tools®. With the inference time as low as 10ms to 250ms, real-time protection can be achieved. This methodology enables reliable detection of series and parallel arcs, mini-arcs under resistive load conditions, and abnormal current profiles—capabilities that traditional analog methods struggle to deliver. The support of DC/DC data capture and model iteration enables quick detection of abnormal current profiles, tampering, and unsafe wiring.
Hardware Approaches for Analog Filtering
GreenPAK™ and AnalogPAK™ programmable mixed-signal devices offer ultra-low power, compact, and configurable analog front-ends that are ideal for high-speed arc fault sensing. With the following features, users can ensure precise AI classification for their products.
- Integrated analog-to-digital converter (ADC), programmable gain amplifier (PGA), comparators, and serial peripheral interface (SPI)
- Low-latency mixed-signal processing
- Hardware level reliability (AEC Q100 options available)
- Flexible signal conditioning for current transformer (CT), shunt, or sensor coil–based detection
- Cost-optimized and footprint-reduced BOM for mass market equipment
GreenPAK filters, shapes, and digitizes the fast-changing arc signature before the signal reaches the MCU, ensuring clean data for artificial intelligence (AI) and machine learning (ML) classification.
- An AFCI turnkey hardware platform provided by Future Electronics enables rapid evaluation and accelerate time-to market. This platform has no cloud dependency. With all inference done at the edge, processing time can be accelerated. There is a one-button learn calibration to accelerate environment tuning with one touch. This platform is scalable for all mass-market OEMs, supporting the different needs. This approach provides several advantages:
- Sensor coil input and signal conditioning board
- High-speed sampling (12-bit ADC at 250kHz)
- RA6M4-based processing with integrated AI model
- One-button learn calibration for fast environment tuning
- No cloud dependency; all inference done at the edge
- Scalable design for mass market OEMs
How the End-to-End AFCI Pipeline System Works
- Current Transformer (CT) or sensor coil captures high-frequency line disturbances
- GreenPAK/AnalogPAK or filters designed with discrete components perform signal filtering, ADC conversion, and SPI streaming
- RA MCU receives data frames and performs:
- Digital signal processing (DSP) preprocessing
- Feature extraction
- Real-time AI classification using Reality AI trained models
- Decision Engine triggers alerts, shutdown, or protection mechanisms
This hybrid architecture is optimized for industrial, consumer, and renewable energy AFCI markets.
Our AFCI platform dramatically reduces development barriers and becomes perfect for solar OEMs, e-mobility devices, battery tools, electric vehicle (EV) chargers, and datacenter PDUs with:
- Faster Time-to-Market - Prevalidated hardware + portable AI models = customers launch AFCI products in weeks, not months.
- Best-in-Class Detection Accuracy - Models trained using Renesas Reality AI tools leverage high-dimensional signal features that are impossible to capture with traditional analog circuitry alone.
- Cost Optimization - GreenPAK consolidates many discrete components into one IC, reducing PCB area, cost, power consumption, and supply chain complexity.
Electrical arcs are a growing global safety challenge. With our practical, high-accuracy, and scalable AFCI platform, users can prevent dangerous electrical arcs from occurring in their applications. Renesas provides everything you need, from silicon to software to comprehensive reference designs to build the next-generation of safe, intelligent power systems in applications such as solar inverters, photovoltaics (PV), battery energy storage systems, EV chargers and infrastructure, AI datacenters, e-mobility, industrial equipment, smart homes, and electrical protection.
Request a Reality AI Demo or start a one-month trial with the Reality AI Explorer Tier.