Spatial graphic relation-based spatiotemporal fuzzy model for large-region distributed parameter systems and its application in lithium-ion batteries
Many thermal processes, described by distributed parameter systems (DPSs), work in a large-scale operation region. In each region, it has special nonlinear dynamics due to specific relative position with heat sources . Achieving a global dynamic model of this kind of processes is extremely difficult due to different local dynamic features. Here, a spatial graphic relation-based spatiotemporal fuzzy modeling method is proposed to reconstruct the model of the large-region DPSs. First, a spectral clustering strategy is developed for region division, where the large-scale spatiotemporal region is divided into several local regions. For each local region, the spatial basis functions (SBFs) are extracted to represent the energy exchange on space. To reflect the global spatial feature , an incremental fuzzy fusion approach is designed and integrates these SBFs to form a global spatial function. Then, the temporal dynamics is obtained by projecting the spatiotemporal data on this global spatial function and characterized by a fuzzy model. Integrating the global spatial function and temporal model, the spatiotemporal model is constructed for the process with large-scale operation region. Using theoretical analysis and experiment, modeling ability of the proposed model is demonstrated effectively. • A spectral clustering strategy is developed for region division, where the large-scale spatiotemporal region is divided into several local regions. • An incremental fuzzy fusion approach is designed and integrates these SBFs of each local region to form a global spatial function reflecting the global spatial dynamics. • The spatiotemporal model is constructed for the dynamics of DPSs with large-scale operation region, by integrating the global spatial function and T-S fuzzy-based temporal model. • Modeling ability of the proposed model is demonstrated by two thermal examples using an experimental platform for the charging/discharging of Lithium-ion batteries.
Authors
- Bowen Xu (ORCID: https://orcid.org/0000-0002-0704-2241)
- Xinjiang Lu (ORCID: https://orcid.org/0000-0002-5100-1092)
- Weiqi Yang (ORCID: https://orcid.org/0000-0003-2122-7442)
- Yunxu Bai (ORCID: https://orcid.org/0000-0003-1601-7184)
Institutions
- Central South University (CN)
- National University of Defense Technology (CN)
- University of South China (CN)
Publication Details
- Journal
- Energy
- Published
- 2025-04-04
- DOI
- https://doi.org/10.1016/j.energy.2025.135921
- Citations
- 2
- Primary Topic
- Multi-Criteria Decision Making
- Type
- article
- Field-Weighted Citation Impact
- 4.21
Funders
- National Natural Science Foundation of China