Three-Minute Battery Health Test Cuts Screening Cost by 80 Percent

A University of New South Wales prototype can grade a lithium-ion cell's health in under three minutes, at a target cost below $25 per EV battery pack — roughly 80 percent cheaper than the roughly $120 that today's full charge-discharge testing commands.

The claimed speed gain is 95.5 percent against incumbent methods. That matters because current used-battery testing relies on an approximately 10-hour full charge-discharge process, which carries a second cost beyond time: damaged cells cycled under hours of high stress can overheat and catch fire.

The platform, developed by researchers at UNSW Sydney, works by sending short electrical pulses through each cell and measuring the response. Statistical models then estimate the battery's state of health. Laboratory testing has shown accuracy above 90 percent. The technology is designed to work with the management systems recyclers and energy storage operators already run, and it covers the three main lithium-ion chemistries used in electric vehicles and stationary storage: lithium iron phosphate (LFP), nickel cobalt aluminium (NCA) and nickel manganese cobalt (NMC).

Why does throughput matter for the material stream?

Associate Professor Huadong Mo of the UNSW School of Systems and Computing frames the problem at the fleet level. As more EVs reach end of life, Australia has a real opportunity to build a local second-life battery industry, with retired packs supporting grid and community energy storage.

The recovery arithmetic is the striking part. "Up to 95% of a battery's components can be recovered, some even to make new batteries. Yet only a small fraction of lithium-ion batteries in Australia are collected for recycling today," Mo said.

A ten-hour test per pack does not scale to that inflow. A three-minute one might.

What is actually being built, and by whom?

The announced project — and it is announced, not built — is a $1.3 million collaboration between UNSW and Malaysia-headquartered battery recycling and lifecycle management company DY New Energy. The partners will test the technology on more than 500 batteries in real-world conditions before any deployment in recycling facilities or second-life storage systems.

The sequence has three stages:

• Field validation — the 500-plus battery trial with DY New Energy under real operating conditions.
• Decision engine — a machine learning-powered tool, to be developed and tested before piloting, that recommends whether a retired battery goes to reuse or to recycling.
• Integration — a Battery Management System (iBMS) module that will embed the platform's insights directly into battery systems for real-time monitoring and decision support.

Dr Ziyang Lyu of the UNSW School of Mathematics and Statistics, the research lead, said the models were built for the messy reality of recycler intake. "One day it might be LFP cells, the next a mix of nickel-based chemistries from different manufacturers. We've designed our models to handle that variety, so the platform works with the batteries operators actually receive, not just ideal lab samples," Lyu said.

Lyu also pointed to the stationary storage fleet as a future demand pool. "This technology could also support the future reuse and recycling of Australia's rapidly expanding fleet of stationary energy storage systems, contributing to a more sustainable and circular battery economy," he said.

Who is paying, and what comes next?

The project carries support through the Trailblazer for Recycling and Clean Energy (TRaCE) Lab to Market Fund. Separately, DY New Energy announced on 13 November 2026 that it will partner with the Australian Research Council's Fire Resilience Infrastructure, Assets and Safety Advancements (FRIASA) Hub to advance safe and scalable battery recycling — a pairing that aligns with the fire-risk problem the pulse method is designed to sidestep.

The economics remain targets until the field data arrives. Lab accuracy above 90 percent is a start; whether it holds across 500 mixed-chemistry batteries in operating conditions is the question the $1.3 million trial exists to answer. The milestone to watch is the completion of that trial and the first piloting of the decision engine inside a working recycling facility. Until then, this is promising instrumentation, not deployed capacity.