Techno-economic modelling and optimization of second life battery packs, with a particular focus on accommodating inhomogeneities and module-to-module variations

This doctoral research presents an in-depth analysis of the development and technoeconomic evaluation of an optimized controller for second-life battery (SLB) packs, integrating heterogeneous State of Health (SOH) modules. The study begins by identifying prevalent lithium-ion battery chemistries and establishing a comprehensive modelling framework. Performance characterization is conducted using Hybrid Pulse Power Characterization (HPPC) tests, with a second-order equivalent circuit model (ECM) achieving a maximum error of 2% and an integrated thermal model with a 15% error. One of the key contributions of this research is the development of a mathematical model for SLBs from cell to pack level, incorporating an offline SOH estimation method. This model enables the development of BMS algorithms specifically designed for SLBs and allows for accurate estimation of the remaining life of the battery pack, leading to more precise techno-economic assessments. Using experimental degradation data, a comprehensive battery model is developed, integrating a neural-network-based SOH estimation algorithm for offline estimation of battery health. The ECM is scaled up from cell to module and pack levels using a lumped parameter methodology. A novel active SOH balancing controller is designed to manage heterogeneous module health, with optimization conducted via Design of Experiments (DOE) and Box-Behnken methods. Sensitivity analysis identifies key control parameters affecting total stored energy (TSE), maximum cell temperature (targeted at 304K), and SOH evolution. Techno-economic analysis demonstrates that employing the proposed optimized controller increases total energy exchange by 142.8% over 1400 cycles. Cost savings of up to £2500 are achieved in this period, with a payback period of approximately four years. Over 2800 cycles (~7.5 years), the cumulative cash flow analysis reveals a profit of ~£3000 if the SOH ageing knee shifts to 56%. The controller enhances SLB performance, reduces energy losses, and extends battery lifespan, offering a sustainable and economically viable solution for second-life applications.

Grantor dc:publisher

Oxford Brookes University

Author dc:creator

• Salek, Farhad

Contributors dc:contributor

• Resalati, Shahaboddin
• Morrey, Denise
• Henshall, Paul

Statement dc:rights

• All rights reserved

Language dc:language

en

DOI dc:identifier

https://doi.org/10.24384/s2ry-w459

OAI identifier oai:identifier

tle:cdfc5909-f793-4626-ad64-ff5fc6f04937:d6bd9758-527a-46cd-bfe2-c433766e8fca:1