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In this chapter, a client-edge-cloud hierarchical federated learning (FL) model has been developed for driving range estimation (DRE) of battery electric vehicles (BEV). Generalized models are aggregated on the cloud server, while customized models trained on local data with similar data distribution are aggregated on the edge server, which mitigates the impact of data heterogeneity.

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Client Selection in Hierarchical Federated Learning with Mean Field Game

  • 章节

  • 发表日期：

    2025年

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  • Yuhan Kang,
  • Hao Gao,
  • Zhu Han

摘要

In this chapter, a client-edge-cloud hierarchical federated learning (FL) model has been developed for driving range estimation (DRE) of battery electric vehicles (BEV). Generalized models are aggregated on the cloud server, while customized models trained on local data with similar data distribution are aggregated on the edge server, which mitigates the impact of data heterogeneity.