Battery Manufacturing Control: The Role of Modelling and software in the Manufacturing Process

Presenter: Dr Mona Faraji Niri, Assistant Professor – Energy Systems, WMG, University of Warwick
Topic: The Role of Modelling and software in the manufacture of batteries
Date: 21st February 2024
Time: 18:30 for 18:40 lecture start
Location: Webinar – the recording of this meeting is available from this link


Battery manufacturing is made up of various processes including: mixing the material, coating, calendering, and drying of the electrodes, cutting and assembly of the cathode, anode and separators, filling with electrolyte and finally the formation and testing.

The large number of parameters involved in each step of the Lithium-ion (li-ion) electrode manufacturing process, as well as the complex electrochemical interactions in those, affect the properties of the final products which are the electrodes and the cells. Control and optimization of the manufacturing process, although very challenging, is critical for reducing the production time, cost, and carbon footprint. Traditionally, this optimisation has been performed via trial-and-error, which is associated with a huge waste and not in line with the net zero future goal.

Data-driven models offer a solution for this manufacturing control and optimization problem and underpin future aspirations for manufacturing volumes. In this context, machine-learning approaches when built upon the experimental data, can serve well for the purpose of predicting final battery performance and relating the cell characteristics to the manufacturing settings to be able to determine them.

This talk will cover the li-ion battery manufacturing steps, modelling requirements, challenges, and the impact of the transparency achieved by machine learning optimisation on the battery industry.

Dr Mona Faraji Niri is a research-focused Assistant Professor of Battery Modelling at WMG, University of Warwick. She was awarded her PhD in control engineering from Iran University of Science and Technology (IUST), and was a postdoctoral researcher in IUST, and a Senior Lecturer in Pooyesh Institute of Higher Education before joining WMG.

Mona is a research fellow of the Faraday Institution, which empowers Britain’s Battery Revolution. She is a Fellow of the Alan Turing Institution in Artificial Intelligence and Data science, and a MIET member. She also holds a Fellowship from the Higher Education Academy (FHEA). She is specialised in modelling, control and machine learning algorithms and has extensive experience in energy storage systems, li-ion batteries, battery management as well as electric vehicle powertrain. Her research interests also cover areas in optimization of battery manufacturing processes via machine learning, and artificial intelligence.

Mona has been endorsed as Future Promise in this field by the Royal Academy of Engineering in 2021. She was the recipient of the TechWomen100 UK award in 2021 and recognised as WMG early career researcher of the year for 2022. Mona’s research on the application of AI for li-ion battery manufacturing was selected to receive the postdoctoral research excellence award in 2022 and put her in the shortlist of the IET Sir Henry Royce achievement medal.

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