Testing Battery Parameters and Estimate Strategies for Electrical Vehicle

Abstract

In the fast-growing market of Electrical Vehicles (EV), the State of Charge (SOC) of the battery is an important indicator of battery capacity. For designing the model of the battery, parameter estimation is a very important aspect to be considered in electric vehicles. The determination of SOC and other battery parameters is a challenging task for which there is a need to develop a technique for accurate estimation of these parameters. Researchers are working to find methods to reduce both the time needed for battery parameter estimation and the number of times the experiments must be conducted. Universal Adaptive Stabilization (UAS) methodology is one such technique that yields accurate estimations while simultaneously reducing the number of iterations to converge toward the true value. UAS technique is one of the best methods which can be easy to use for estimating other parameters of the battery model like output terminal voltage and series resistance as well. An important component of the UAS technique is a switching function. A particular class of switching functions, the Nussbaum type function, having Mittag-Leffler (ML) form, is discussed within this paper. This paper also presents a way to implement this technique successfully on a small electric vehicle (EV) prototype with continuous recalibrations done during run-time.