Integrated Modeling for Intelligent Battery Thermal Management

Effective thermal management is crucial to the optimal operation of lithium ion batteries and its health management. However, the thermal behaviors of batteries are governed by complex chemical process whose parameters will degrade over time and different environment. Furthermore, limited sensors exist for measurement of the spatiotemporal thermal process. In this paper, an intelligent model for online estimation of the temperature distribution in lithium ion battery systems is proposed. Due to the difficulty and high cost to identify the online operational model directly from practical experiment measurement, an integrated approach is developed to derive the approximate analytical model through hierarchical modeling from experiment, simulation, and intelligent learning. The proposed model could be easily added to the existing battery management system.