Real-Time Estimation of 2-D Temperature Distribution in Lithium-Ion Pouch Cells

Abstract

Thermal management is an integral part of battery management systems due to the effect of temperature on safety, lifetime, and efficiency of batteries. Therefore, a reliable real-time estimation algorithm is required to estimate the temperature distribution in battery cells based on available measurements. Temperature estimation in pouch-type cells is especially challenging due to the nonuniform distribution along length and breadth. Motivated by this issue, we study effective sensor placement and estimation algorithm design for pouch cells in this article. Specifically, we explore two scenarios: Scenario 1 where multiple temperature sensors are available, and Scenario 2 where only one temperature sensor is available. For Scenario 1, we find the minimum number of sensors required and their effective locations, whereas for Scenario 2, we find the effective location of the single sensor that maximizes the state observability. We employ the Gramian observability analysis for this study. Subsequently, we design sliding mode observer-based real-time algorithms for distributed temperature estimation in both scenarios. Finally, we illustrate the performance of the proposed estimation algorithms through extensive experimental and simulation studies.