Temperature Dependent Parameter Estimation of Electrical Vehicle Batteries

• Main Authors: Anna I. Pózna, Katalin M. Hangos, Attila Magyar
• Format: Article
• Language: English
• Published: MDPI AG 2019-09-01
• Series: Energies
• Subjects: dynamic modeling; thermal management; parameter estimation; energy storage operation and planning; electric and solar vehicles
• Online Access: https://www.mdpi.com/1996-1073/12/19/3755

Parameter estimation of electrical vehicle batteries in the presence of temperature effect is addressed in this work. A simple parametric temperature dependent battery model is used for this purpose where the temperature dependence is described by static relationships. A two-step method is used that includes a parameter estimation step of the key parameters at different temperatures followed by a static optimization step that determines the temperature coefficients of the corresponding parameters. It was found that the temperature dependent parameter characteristics can be reliably estimated from charging profiles only. The proposed method can be used as a computationally effective way of determining the key battery parameters at a given temperature from their actual estimated values and from their previously determined static temperature dependence. The proposed parameter estimation method was verified by simulation experiments on a more complex battery model that also describes the detailed dynamic thermal behavior of the battery.