Efficient Fault Diagnosis in Lithium-Ion Battery Packs: A Structural Approach with Moving Horizon Estimation
Journal:
arXiv
Published Date:
Mar 1, 2025
Abstract
Safe and reliable operation of lithium-ion battery packs depends on effective
fault diagnosis. However, model-based approaches often encounter two major
challenges: high computational complexity and extensive sensor requirements. To
address these bottlenecks, this paper introduces a novel approach that
harnesses the structural properties of battery packs, including cell uniformity
and the sparsity of fault occurrences. We integrate this approach into a Moving
Horizon Estimation (MHE) framework and estimate fault signals such as internal
and external short circuits and faults in voltage and current sensors. To
mitigate computational demands, we propose a hierarchical solution to the MHE
problem. The proposed solution breaks up the pack-level MHE problem into
smaller problems and solves them efficiently. Finally, we perform extensive
simulations across various battery pack configurations and fault types to
demonstrate the effectiveness of the proposed approach. The results highlight
that the proposed approach simultaneously reduces the computational demands and
sensor requirements of fault diagnosis.
