A Unified Model for Active Battery Equalization Systems

TL;DR

This paper introduces a hypergraph-based unified model for active battery equalization systems, enabling systematic analysis, comparison, and optimization of equalizer configurations to improve battery pack performance.

Contribution

The paper presents the first unified hypergraph model for battery equalization systems, linking system structure to performance metrics and simplifying design optimization.

Findings

Equalization time is inversely related to the hypergraph Laplacian's second smallest eigenvalue.

Controllability analysis provides necessary conditions for system balancing.

The model effectively predicts equalization performance, reducing reliance on experiments.

Abstract

Lithium-ion battery packs demand effective active equalization systems to enhance their usable capacity and lifetime. Despite numerous topologies and control schemes proposed in the literature, conducting quantitative analyses, comprehensive comparisons, and systematic optimization of their performance remains challenging due to the absence of a unified mathematical model at the pack level. To address this gap, we introduce a novel, hypergraph-based approach to establish the first unified model for various active battery equalization systems. This model reveals the intrinsic relationship between battery cells and equalizers by representing them as the vertices and hyperedges of hypergraphs, respectively. With the developed model, we identify the necessary condition for all equalization systems to achieve balance through controllability analysis, offering valuable insights for selecting the number of equalizers. Moreover, we prove that the battery equalization time is inversely correlated with the second smallest eigenvalue of the hypergraph's Laplacian matrix of each equalization system. This significantly simplifies the selection and optimized design of equalization systems, obviating the need for extensive experiments or simulations to derive the equalization time. Illustrative results demonstrate the efficiency of the proposed model and validate our findings.