Moment Energy Achieves UL Certification for Second Life Battery Management System

May 19, 2026
Moment Energy has received UL 60730-1 certification for its battery management system designed for repurposed EV batteries, marking the first such certification globally and setting a new standard for safety in second life battery storage applications.

Moment Energy has become the first company to receive UL 60730-1 functional safety certification for a battery management system designed for repurposed electric vehicle batteries, announced in a press release. The certification from UL Solutions establishes a verified safety benchmark for second life battery storage systems.

The certified system manages performance and safety for reused EV batteries while maintaining compliance with intellectual property agreements from original equipment manufacturers. It enables these batteries to meet safety standards required for energy infrastructure, including data centers and utilities.

This certification complements Moment Energy's existing compliance with UL 1974, UL 1973, and UL 9540. It simplifies permitting and insurance processes for commercial and industrial deployments such as microgrids, EV charging hubs, and data centers.

Moment Energy stated that the certification also supports its use of AI and machine learning for system optimization, ensuring that all safety-critical functions remain independently verified under certified standards.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Silicon Brief, Industrial AI Weekly or Daily AI Brief.

Also, consider following us on social media:

AI Chips & Datacenters AI Brief AI Brief (X)
Free newsletter

Silicon Brief

Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.