Online Sensorless Temperature Estimation of Lithium-Ion Batteries Through Electro-Thermal Coupling
Yusheng Zheng, Yunhong Che, Xiaosong Hu, Xin Sui, Remus Teodorescu
Abstract
Owing to the nonnegligible impacts of temperature on the safety, performance, and lifespan of lithium-ion batteries, it is essential to regulate battery temperature to an optimal range. Temperature monitoring plays a fundamental role in battery thermal management, yet it is still challenged by limited onboard temperature sensors, particularly in large-scale battery applications. As such, developing sensorless temperature estimation is of paramount importance to acquiring the temperature information of each cell in a battery system. This article proposes an estimation approach to obtain the cell temperature by taking advantage of the electrothermal coupling effect of batteries. An electrothermal coupled model, which captures the interactions between the electrical and the thermal dynamics, is established, parameterized, and experimentally validated. A closed-loop observer is then designed based on this coupled model and the extended Kalman filter to estimate the battery temperature by merely using the voltage measurement as feedback. The electrothermal coupling effect enables the full observability of batteries’ internal states from their voltage, and contributes to an accurate and robust temperature estimation. The capability of the proposed estimation method has been demonstrated via experiments, with root-mean-square error less than 0.7 °C in various scenarios.