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MEMESIS / RESEARCH

Researching the Safety of the Battery Afterlife.

Our research focuses on understanding what happens inside batteries as they age — and how those changes affect their safety, reliability and suitability for second-life use.

Research focus / Technology under development
Gloved technician lifting a module from an opened electric vehicle battery packTHE NEXT LIFE STARTS WITH UNDERSTANDING.

01 / RESEARCH AREAS

Looking inside. Thinking ahead.

Six connected areas of investigation, guided by the condition and safety of retired batteries.

A.
RESEARCH FOCUS

Battery Health & Degradation

Understanding how battery condition changes over its first life, and what remains at retirement.

  • SOH estimation
  • SOC estimation
  • Ageing characterisation
  • Parameter identification
  • Impedance behaviour
B.
RESEARCH FOCUS

Battery Pack Diagnostics

Looking beyond overall pack performance to reveal the differences between cells and modules.

  • Cell inconsistency
  • Module-level anomaly detection
  • Pack-level masking effects
  • Fault localisation
C.
RESEARCH FOCUS

Internal Short Circuit Detection

Researching early electrical signatures of internal faults in batteries with different ageing histories.

  • Soft ISC
  • Early ISC
  • Ageing-aware ISC detection
  • Fault localisation
  • Electrical fault modelling
D.
RESEARCH FOCUS

Retired Battery Safety

Connecting health indicators with the electrical and thermal risks relevant to a battery’s next application.

  • State of safety
  • Thermal risk
  • Electrical risk
  • Second-life qualification
E.
RESEARCH FOCUS

Battery Modelling

Building interpretable representations of battery behaviour to support diagnosis and investigation.

  • Equivalent circuit models
  • 2RC ECM
  • Parameter estimation
  • Digital twins
  • Physics-informed models
F.
RESEARCH FOCUS

Data-Driven Battery Intelligence

Exploring how battery data can become useful evidence for safer downstream decisions.

  • Machine learning
  • Transfer learning
  • Domain adaptation
  • Anomaly detection
  • Decision support

02 / RESEARCH PIPELINE

From battery data to decision support.

A connected research framework. Each stage adds understanding; validation and uncertainty remain central throughout.

  1. 01Battery Data
  2. 02Modelling
  3. 03Feature Extraction
  4. 04Health Assessment
  5. 05Fault Detection
  6. 06Safety Assessment
  7. 07Decision Support

Conceptual research pipeline — not a claim of a validated commercial system.

03 / PUBLICATIONS & PROJECTS

Science worth sharing.

Research outputs coming soon.

Publications and project updates will be added when they are ready to share.

Discuss a research collaboration

A BETTER NEXT LIFE

Have retired EV batteries?
Let’s understand what
they can become.

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