Data-driven Modeling of Li-ion Battery based on the Manufacturer Specifications and Laboratory Measurements

Having a good model for a Li-ion battery is essential in the development and testing of state estimation and lifetime prediction algorithms. The desired features of the model include flexibility, fast development, accuracy and reliability. There are many different ways to model a battery, depending on the level of abstraction desired, the data available and the target simulation environment. In this paper we focus on how to build a battery model using a data-driven approach. We present two different ways of creating the model: using datasheets provided by the manufacturer and using more extensive laboratory measurements. This hybrid method of using lab data on datasheet battery model is named here as advance datasheet battery model. We present a thorough report on the successful preparation of the data to be used in both models, and highlight the benefits and the disadvantages of both approaches. Furthermore, we show how the measurements-based advanced datasheet battery model is more robust to model battery behavior with 100% improvement in modeling accuracy compared to a pure datasheet based approach.