Battery Degradation

Using a suite of advanced modelling and characterisation techniques, the project aims to understand the mechanisms of degradation of lithium-ion batteries containing high Ni-content NMC and graphite.

This project is examining how environmental and internal battery stresses (such as high temperatures, charging and discharging rates) degrade electric vehicle (EV) batteries over time. Results will include the optimisation of battery materials and cells to extend battery life (and hence EV range) and reduce battery costs.

Despite the recent reduction in cost of lithium-ion batteries driven by mass manufacture, the widespread adoption of battery electrical vehicles is still hindered by cost and durability, with the lifetimes of the batteries falling below the consumer expectation for long-term applications such as transport.

Additionally, fast charging of battery electric vehicles is crucial to help assuage range anxiety and provide the operational convenience required for mass adoption of the technology. Fast charging, however, can rapidly accelerate degradation and even trigger degradation mechanisms that are not present in ‘normal’ operating conditions. A key goal for the automotive industry is to understand more fully the causes and mechanisms of degradation to enable improved control and prediction of the state-of-health of battery systems.

The goal of the project is to create accurate models for use by the automotive industry to extend lifetime and performance.

Case Study: Accurate Battery Forecasting

Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved challenge that limits technologies such as consumer electronics and electric vehicles.

The Degradation team has built an accurate battery forecasting system by combining electrochemical impedance spectroscopy (EIS)—a real-time, non-invasive, and information-rich measurement that is previously underused in battery diagnosis —with Gaussian process machine learning.

Over 20,000 EIS spectra of commercial Li-ion batteries were collected at different states of health, states of charge, and temperatures —the largest dataset to our knowledge of its kind.

The Gaussian process model takes the entire spectrum as input, without further feature engineering, and automatically determines which spectral features predict degradation.

This model accurately predicts the remaining useful life, even without complete knowledge of past operating conditions of the battery.

The results demonstrate the value of EIS signals in battery management systems. This has multiple potential benefits, such as improving the economics of grid-based storage, assessing the length of second life batteries, and measuring the wear and tear on electric vehicles.

Project presentation from the Faraday Institution Conference, November 2021


  • Build a significantly enhanced scientific understanding of the fundamental degradation mechanisms in modern, nickel-rich Li-ion battery chemistries.  
  • Develop the capabilities, tools, and techniques required to fully characterise/quantify the chemical and physical degradation mechanisms within nickel-rich Li-ion batteries, including the complex interplay between individual mechanisms.  
  • Work with industry partners to translate and commercially exploit the knowledge, understanding, and potential intellectual property generated 


In one example of Faraday Institution research moving to the next stage of commercialisation, the SABRE project, selected as one of the Faraday Battery Challenge Round 4 projects in what was a highly competitive bidding process, leverages the knowledge, capabilities and know-how developed by UCL’s Electrochemical Innovation Lab and refined as part of the Faraday Institution extending battery life project.

Project funding
1 March 2018 – 31 March 2023
Principal Investigator
Professor Clare Grey
University of Cambridge

Project Leaders
Dr Rhodri Jervis
University College London
Dr David Hall
University of Cambridge
University Partners
University of Cambridge (Lead)
University of Birmingham
University College London
Imperial College London
University of Liverpool
University of Oxford
University of Sheffield
University of Southampton
University of Warwick
Research Organisations, Facilities and Institutes
National Physical Laboratory (NPL)
+ 8 Industrial Partners


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