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<p>Solid-state batteries (SSBs) promise higher energy density and intrinsic safety than lithium-ion batteries, but field-scale deployment is blocked by life cycle-wide barriers that materials-centric research alone cannot resolve. Interfacial degradation, poor real-world reliability and complex end-of-life recovery differ across oxide, sulfide and polymer chemistries. These barriers call for a system-level rather than a materials-level response. Electrical engineering supplies the missing toolkit: multi-physics sensing, machine-learning analytics and adaptive control coupled to the life cycle digital twin. These capabilities form a continuous information loop across the SSB’s life cycle. The life cycle intelligence framework treats the cell as a cyber-physical system rather than a sealed storage device. In this Review, we examine the framework’s components, identify the engineering and institutional challenges that hinder scale-up, and outline a three-phase roadmap towards commercial deployment.</p>

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Life cycle intelligence for solid-state batteries

  • 期刊论文

  • 发表日期：

    2026年8月4日

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  • Yi Chen,
  • Ji Qian,
  • Yu Li,
  • Li Li,
  • Chengwei Xiao,
  • Feng Wu,
  • Renjie Chen

摘要

Solid-state batteries (SSBs) promise higher energy density and intrinsic safety than lithium-ion batteries, but field-scale deployment is blocked by life cycle-wide barriers that materials-centric research alone cannot resolve. Interfacial degradation, poor real-world reliability and complex end-of-life recovery differ across oxide, sulfide and polymer chemistries. These barriers call for a system-level rather than a materials-level response. Electrical engineering supplies the missing toolkit: multi-physics sensing, machine-learning analytics and adaptive control coupled to the life cycle digital twin. These capabilities form a continuous information loop across the SSB’s life cycle. The life cycle intelligence framework treats the cell as a cyber-physical system rather than a sealed storage device. In this Review, we examine the framework’s components, identify the engineering and institutional challenges that hinder scale-up, and outline a three-phase roadmap towards commercial deployment.