State-space model with coordinate attention enhances lithium-ion battery remaining useful life prediction
Peer-Reviewed Publication
Updates every hour. Last Updated: 21-Oct-2026 14:16 ET (21-Oct-2026 18:16 GMT/UTC)
Researchers have developed a coordinate‑aware Mamba2 framework (CA‑Mamba2) for predicting the remaining useful life of lithium‑ion batteries. By integrating a coordinate feature attention network and a swiGLU‑gated residual network with the state‑space Mamba2 backbone, the model effectively captures both long‑term degradation trends and local fluctuation patterns. On the NASA, Tongji University, and Xi’an Jiaotong University datasets under single‑variable, multivariate, and cross‑dataset generalization settings, the model achieved mean absolute error values below 0.0098, 0.0016, and 0.0083, respectively, with superior computational efficiency and robustness across different prediction starting points.
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