Parameterization and Observability Analysis of Scalable Battery Clusters for Onboard Thermal Management

Parameterization and Observability Analysis of Scalable Battery Clusters for Onboard Thermal Management — Thermal management is an important issue for lithium ion batteries, as overheating may result in disastrous consequences. Although the battery surface temperature is commonly measured, the core temperature of a cell may be much higher hence more critical. The core temperature of a battery, though unmeasurable, can be estimated by an observer, based on a battery thermal model and the measurement of the current and the surface temperature. To enable accurate estimation of the core temperature, the model parameters need to be correctly identified. For such purpose, an online parameterization methodology and an adaptive observer are designed based on a cylindrical battery thermal model in this paper. The single cell thermal model is then scaled up to create a battery cluster model to investigate the temperature pattern of the cluster. The modeled thermal interconnections between cells include cell to cell heat conduction and thermal dynamics of the coolant flow due to convection. An observability analysis is performed on the cluster in order to design a closed loop observer. Based on the analysis, guidelines for sensor deployment are derived that guarantee observability of all temperature states.