Experimental and Numerical Study for Temperature Estimation in Lithium-Ion Cells Using Taguchi-Based Model Parameterization

Abstract

Precise modelling of Li-ion batteries is essential for ensuring their dependable and efficient operation, and temperature prediction is closely related to model accuracy, which is the main aim of this study. Among various battery models, the equivalent circuit model (ECM) is the most prevalent, often employing the hybrid pulse power characteristic (HPPC) test for parameter identification. This paper presents an experimental and numerical investigation into temperature estimation for lithium-ion cells using model parametrization based on the Taguchi method. Four key HPPC test parameters-pulse time gap, discharge pulse time, discharge pulse C rate, and rest time-are analysed for their effects on the performance of an ECM across various operating temperatures (-10 degrees C, 25 degrees C, 40 degrees C). The methodology involves a systematic HPPC test design using the Taguchi method, followed by detailed parameter identification. The ECM parameters obtained from these HPPC profiles are further analysed numerically using Fluent software. The study provides a more precise representation of the battery's performance in real-world applications by developing models specific to each temperature and discharge rate. A comparison is made between the numerical and experimental results across different operating temperatures and discharge rates (1C, 3C, 5C, and 7C). The Analysis of Variance (ANOVA) was employed to evaluate the influence of these parameters on battery cell temperature accuracy. The results showed the critical role of discharge pulse C-rate across all temperatures, while also indicating that pulse time gap becomes increasingly important at higher temperatures and discharge rates, whereas discharge pulse time and rest time are more influential at lower temperatures and discharge rates.