Topic
State of charge
About: State of charge is a research topic. Over the lifetime, 12013 publications have been published within this topic receiving 201419 citations. The topic is also known as: SoC & SOC.
Papers published on a yearly basis
Papers
More filters
TL;DR: In this paper, an open-loop optimal control scheme was proposed to incorporate the operating constraints of the battery energy storage system (BESS), such as state of charge limits, charge/discharge current limits, and lifetime.
Abstract: Integrating a battery energy storage system (BESS) with a large wind farm can make a wind farm more dispatchable. This paper focuses on development of a control strategy for optimal use of the BESS for this purpose. The paper considers an open-loop optimal control scheme to incorporate the operating constraints of the BESS, such as state of charge limits, charge/discharge current limits, and lifetime. The goal of the control is to have the BESS to provide as much smoothing as possible, so that the wind farm can be dispatched on an hourly basis based on the forecasted wind conditions. The effectiveness of this control strategy has been tested by using an actual wind farm data. Furthermore, a real-time implementation strategy using model predictive control is also proposed. Finally, it is shown that the control strategy is very important in improving the BESS performance for this application.
327 citations
TL;DR: In this paper, a dual filter consisting of an interaction of a standard Kalman filter and an Unscented Kalman Filter is proposed to predict internal battery states and a support vector machine (SVM) algorithm is implemented and coupled with the dual filter.
326 citations
TL;DR: A nonlinear autoregressive with exogenous inputs (NARX) architecture of the DDRN is designed for both state of charge (SOC) and state of health (SOH) estimation.
Abstract: This paper presents an application of dynamically driven recurrent networks (DDRNs) in online electric vehicle (EV) battery analysis. In this paper, a nonlinear autoregressive with exogenous inputs (NARX) architecture of the DDRN is designed for both state of charge (SOC) and state of health (SOH) estimation. Unlike other techniques, this estimation strategy is subject to the global feedback theorem (GFT) which increases both computational intelligence and robustness while maintaining reasonable simplicity. The proposed technique requires no model or knowledge of battery's internal parameters, but rather uses the battery's voltage, charge/discharge currents, and ambient temperature variations to accurately estimate battery's SOC and SOH simultaneously. The presented method is evaluated experimentally using two different batteries namely lithium iron phosphate ( $\text{LiFePO}_4$ ) and lithium titanate ( $\text{LTO}$ ) both subject to dynamic charge and discharge current profiles and change in ambient temperature. Results highlight the robustness of this method to battery's nonlinear dynamic nature, hysteresis, aging, dynamic current profile, and parametric uncertainties. The simplicity and robustness of this method make it suitable and effective for EVs’ battery management system (BMS).
325 citations
TL;DR: In this article, an online, simple, training-free, and easily implementable scheme that is capable of estimating open-circuit voltage (OCV) and internal resistance of the battery is developed.
324 citations
TL;DR: In this paper, the entropy changes in various cathode and anode materials, as well as in complete Li-ion batteries, were measured using an electrochemical thermodynamic measurement system (ETMS).
323 citations