Asahi Kasei Current Sensors Power EV Charging and Energy Storage Systems
As electric vehicle adoption accelerates and energy storage systems become more common in homes and businesses, the electronics that keep these systems safe are drawing renewed attention. Asahi Kasei Microdevices has announced that its CZ39 and CZ3K current sensors are now featured in a machine learning based arc fault detection reference design from Microchip Technology, a development aimed at improving safety in EV charging stations and energy storage applications.
About Asahi Kasei Microdevices
Asahi Kasei Microdevices (AKM) is a semiconductor manufacturer and a subsidiary of Asahi Kasei Corporation, a diversified Japanese company with operations spanning materials, homes, and health care. AKM specializes in sensor technologies, including Hall-effect current sensors, magnetic sensors, and analog ICs used across automotive, industrial, and consumer electronics markets. The company has built a reputation for precision sensing solutions that support power management and safety systems in demanding applications.
Understanding the Reference Design
Microchip Technology, a supplier of microcontrollers and semiconductor solutions, developed the reference design to address a growing challenge in electrical systems: detecting arc faults before they lead to fires or equipment damage. Arc faults occur when electrical current jumps across a gap in a conductor, often due to damaged wiring, loose connections, or component wear. These faults can generate intense heat and pose serious fire risks, particularly in high-power systems like EV chargers and battery storage units.
The reference design uses machine learning algorithms to analyze current signals in real time, identifying the subtle signatures that distinguish a genuine arc fault from normal electrical noise. This approach allows for faster and more accurate detection compared to traditional threshold-based methods, which can struggle to differentiate between hazardous arcs and the electrical fluctuations that occur during normal equipment operation.
The Role of AKM’s Current Sensors
At the center of this detection system are AKM’s CZ39 and CZ3K current sensors, which provide the precise current measurements needed for the machine learning model to function effectively. These Hall-effect based sensors are designed to deliver accurate, low-noise current sensing across a range of operating conditions.
- High measurement accuracy to support reliable arc detection algorithms
- Compact form factor suitable for integration into space-constrained power electronics
- Isolation performance that helps maintain safety in high-voltage environments
- Stable output across varying temperatures and load conditions
These characteristics make the sensors well suited for the demanding electrical environments found in EV charging infrastructure and energy storage systems, where current levels can fluctuate significantly and safety margins are critical.
Why This Matters for EV Charging and Energy Storage
EV charging stations, particularly fast chargers, handle substantial electrical loads and are often installed in outdoor or semi-exposed locations where wiring can be subject to wear, moisture, and physical stress over time. Similarly, energy storage systems, whether deployed in residential settings or larger commercial installations, involve high-capacity batteries and power electronics that must be monitored closely to prevent thermal events.
Arc fault detection has become an increasingly important safety feature in these applications as installation volumes grow worldwide. Regulatory bodies and industry standards organizations have placed greater emphasis on fire prevention measures for both EV charging equipment and stationary storage systems, creating demand for detection technologies that can operate reliably without generating false alarms that disrupt normal system operation.
A Combined Approach to Safety
The integration of AKM’s sensors into Microchip’s reference design illustrates how sensor hardware and intelligent software algorithms are increasingly working together to address safety challenges in power electronics. Rather than relying solely on mechanical protection devices or simple current thresholds, this combined approach uses continuous data collection paired with pattern recognition to catch fault conditions earlier.
For manufacturers designing EV chargers or energy storage products, reference designs like this one can shorten development timelines by providing a validated starting point that combines proven sensor components with tested detection algorithms. This can be particularly valuable as the EV charging and storage markets continue to expand and face pressure to bring products to market quickly while still meeting safety requirements.
Looking Ahead
As renewable energy systems and electric vehicle infrastructure continue to scale globally, the demand for reliable safety technologies will likely keep pace. Current sensors like the CZ39 and CZ3K represent a component-level contribution to a larger effort to make high-power electrical systems safer through better monitoring and faster fault detection.
The collaboration between AKM and Microchip on this reference design reflects a broader trend in the electronics industry, where sensor suppliers and system designers are working more closely together to solve specific application challenges. For the EV charging and energy storage sectors, this kind of technical cooperation may help address safety concerns that could otherwise slow adoption, supporting continued growth in both markets.
Analyzed and outlined by Claude Sonnet 5, images by Gemini 3.1 Flash.
**Source** https://www.businesswire.com/news/home/20260908946869/en/Asahi-Kasei-Microdevices-CZ39-and-CZ3K-Current-Sensors-Featured-in-Microchip-Technologys-Machine-Learning-Based-Arc-Fault-Detection-Reference-Design