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.

Charging Pattern Optimization for Lithium-Ion Batteries With an Electrothermal-Aging Model

Abstract: This paper applies advanced battery modeling and multiobjective constrained nonlinear optimization techniques to derive suitable charging patterns for lithium-ion batteries. Three important yet competing charging objectives, including battery health, charging time, and energy conversion efficiency, are taken into account simultaneously. These optimization objectives are first subject to a high-fidelity battery model that is synthesized from recently developed individual electrical, thermal, and aging models. The coupling relationship and multiple timescales among different model dynamics are identified. Furthermore, constraints are imposed explicitly on the current, voltage, state-of-charge, and temperature. Such a complex charging problem is solved by using an ensemble multiobjective biogeography-based optimization approach. As a result, two charging patterns, namely the constant current–constant voltage (CC–CV) and multistage CC–CV, are optimized to balance various combinations of charging objectives. Different tradeoffs and sensitive elements are compared and analyzed based on the Pareto frontiers. Illustrative results demonstrate that the proposed strategy can effectively offer feasible health-conscious charging with desirable tradeoffs among charging speed and energy conversion efficiency under different demand priorities.

Lithium-Ion Battery Parameters and State-of-Charge Joint Estimation Based on H-Infinity and Unscented Kalman Filters

Abstract: Accurate estimation of state-of-charge (SoC) is vital to safe operation and efficient management of lithium-ion batteries Currently, the existing SoC estimation methods can accurately estimate the SoC in a certain operation condition, but in uncertain operating environments, such as unforeseen road conditions and aging related effects, they may be unreliable or even divergent This is due to the fact that the characteristics of lithium-ion batteries vary under different operation conditions and the adoption of constant parameters in battery model, which are identified offline, will affect the SoC estimation accuracy In this paper, the joint SoC estimation method is proposed, where battery model parameters are estimated online using the H-infinity filter, while the SoC are estimated using the unscented Kalman filter Then, the proposed method is compared with the SoC estimation methods with constant battery model parameters under different dynamic load profiles and operation temperatures It shows that the proposed joint SoC estimation method possesses high accuracy, fast convergence, excellent robustness and adaptability

Coordinated Control Strategy of a Battery Energy Storage System to Support a Wind Power Plant Providing Multi-Timescale Frequency Ancillary Services

Abstract: With increasing penetrations of wind generation on electric grids, wind power plants (WPPs) are encouraged to provide frequency ancillary services (FAS); however, it is a challenge to ensure that variable wind generation can reliably provide these ancillary services. This paper proposes using a battery energy storage system (BESS) to ensure the WPPs’ commitment to FAS. This method also focuses on reducing the BESS's size and extending its lifetime. In this paper, a state-machine-based coordinated control strategy is developed to utilize a BESS to support the obliged FAS of a WPP (including both primary and secondary frequency control). This method takes into account the operational constraints of the WPP (e.g., real-time reserve) and the BESS (e.g., state of charge [SOC], charge and discharge rate) to provide reliable FAS. Meanwhile, an adaptive SOC-feedback control is designed to maintain SOC at the optimal value as much as possible, and, thus, reduce the size and extend the lifetime of the BESS. The effectiveness of the control strategy is validated with an innovative multi-area interconnected power system simulation platform that can mimic realistic power systems operation and control by simulating real-time economic dispatch, regulating reserve scheduling, multi-area automatic generation control, and generators’ dynamic response.

Impedance Observer for a Li-Ion Battery Using Kalman Filter

Abstract: Most methods for state-of-charge or state-of-health prognostics are impedance based. Impedance models must be as simple as possible to be implemented on embedded applications but as accurate as possible to represent the main electrochemical phenomena. The parameters of such models can be identified using impedance spectroscopy. However, the electrochemical features change in relation to numerous parameters, such as temperature or aging, which involves updating the model of the battery online. This paper deals with the use of an extended Kalman filter (EKF) for the observation of the parameters of a Li-ion battery lumped model. First, this paper will focus on the electrical model that can be used to represent the main electrochemical phenomena in the battery. Then, mathematical considerations about the EKF are reminded to be applied to the observation of the impedance parameters of the battery. This method has been validated on an urban driving cycle of a hybrid electric vehicle.