PhD Studentship: Innovating Industry Battery Reuse and Recycling through 'Battery as a Service' Business Model

The transition towards renewable energy sources and the electrification of transport underscore the increasing reliance on battery technologies. In the “UK Battery Strategy ” published by the Department for Business & Trade in 2023, it states “Batteries will play an essential role in our energy transition and our ability to successfully achieve net zero by 2050”, and “The Government’s 2030 vision is for the UK to have a globally competitive battery supply chain that supports economic prosperity and the net zero transition.”

Concurrently, this surge in battery usage poses significant sustainability challenges, particularly in terms of waste management and resource depletion. The "Battery as a Service" (BaaS) business model has emerged as a promising approach for transitioning toward a circular battery economy. It shifts the focus from selling batteries to selling battery services, incentivising manufacturers to design for longevity, remanufacture, and responsible end-of-life management [1].

Nevertheless, while BaaS holds significant potential, several research gaps require further exploration.

• Limited understanding of optimal BaaS models for different battery applications: Existing research focuses on passenger Electric Vehicle (EV)s, neglecting the diverse needs of other sectors (e.g., stationary storage, power tools) [2].
• Lack of comprehensive frameworks for assessing the environmental and economic viability of BaaS across the entire battery lifecycle: Existing studies often focus on specific aspects like life cycle assessment (LCA) or economic feasibility but lack integrated frameworks [3].
• Insufficient knowledge on integrating big data and machine learning (ML) for optimising battery use, maintenance, and end-of-life decision-making within BaaS models: The potential of data analytics for maximising battery lifespan and minimising resource losses is underexplored [4].

Therefore, this research aims to develop and evaluate innovative BaaS model incorporating big data and ML for optimising the use, reuse and recycling of batteries across various industry applications.

To achieve the aim, the research objectives are:

• To identify and characterise different BaaS models suitable for diverse industry battery applications.
• To develop a comprehensive framework for assessing the environmental and economic viability of BaaS throughout the battery lifecycle.
• To design and implement ML algorithms for analysing battery health data, predicting remaining useful life (RUL), and optimising BaaS operations for maximising battery reuse and minimising waste.

A quantitative research approach will be employed: (1) A comprehensive literature review, critically analysing existing BaaS models, LCA methods, and ML applications in battery management; (2) Collection of real-world battery performance data from open sources and various industry partners; (3) based on the collected big data, design and train algorithms for predicting battery RUL, optimising decision on retrofit, second life, and recycling by considering environmental, economic and social factors. 

Please review the following link in advance of submitting an application: https://docs.gre.ac.uk/rep/communications-and-recruitment/innovating-industry-battery-reuse-and-recycling-through-battery-as-a-service-business-model