Battery State-of-Charge Estimation Prototype using EMF Voltage Prediction
Sprache des Titels:
Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS 2014)
A reliable knowledge of cell parameters like the state-of-charge (SoC) is essential for the optimization of batterypowered applications. Usually, during relaxation (the phase of no or low loads) the SoC is determined based on the measurement of the battery?s electro-motive force (EMF). To obtain a reliable measurment, it is required that the battery voltage transient is in a well-relaxed state, which is rarely reached in practice (e.g. due to periodic discharge activities). In this paper, a predictive methodology is presented which is able to forecast the EMF and therewith the SoC already during a not well-relaxed state of the voltage transient. A nonlinear relaxation voltage model is reformulated such that the problem can be treated as a linear
least squares estimation problem. Based on this estimation, the
performance is evaluated with respect to the following aspects:
prediction time, current rate influence, SoC influence, cell-to-cell
deviation, or rather aging and temperature effects. Experimental results are presented for a fixed-point implementation of the estimation scheme on a CY8CKIT-050 PSOC5 programmable system on chip. For validation, measurements of 2:25Ah Sanyo UR18650A lithium cells have been used. It is shown that the presented approach offers an improved re-initialization methodology for the Coulomb counting method, and that it clearly outperforms the usual EMF-measurement based SoC determination method.