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.