The proposed variable recursive least square (VRLS) algorithm, tailored for this ECM, continuously updates model battery parameters in real-time, improving …
In this paper, we proceeded to a modelling of the lithium battery based on thevenin model, which is the most used in SOC estimation cases, followed by a parameter identification based on the OCV-SOC curve, and the least square algorithm implemented on Matlab using the nlinfit curve function.
In this study, an improved adaptive robust unscented Kalman Filter (ARUKF) is proposed for an accurate state-of-charge (SOC) estimation of battery management system (BMS) in electric vehicles (EV). The extended Kalman Filter (EKF) algorithm is first used to achieve online identification of the model parameters. Subsequently, the …
It is noticeable that the best value of forgetting factor in RLS is 0.965 for FUDS working condition according to Table 9.To compare the above methods, λ min of FT-RLS, VFFRLS and SDFF-RLS are set to be 0.965, λ max is 0.998, and the initial values of parameters as well as other parameter settings are consistent with UDDS operating …
El Marghichi et al. Period. Polytech. Elec. Eng. Comp. Sci. |3 2 Modeling of the lithium-ion battery The model of the cell employed is represented in Fig. 1.
FFRLS is one of the commonly used online parameter identification algorithms for lithium-ion battery models. By introducing the forgetting factor λ into the RLS algorithm, FFRLS redistributes the weight …
Abstract: A precise estimation of the lithium-ion battery''s inner state, such as the state of health (SoH) and the state of charge (SoC) of the battery, is crucial for a reliable and effective performance of a battery management system in an electric vehicle. In this paper, an improved real-time model-based battery parameters estimation method using the …
The results indicate that the second-order dynamic lithium-ion battery model parameters can effectively simulate charging and discharging process, contribute to reflect the battery performance status, provide support for the efficient management and application of lithium-ion battery. ... through the least square method. Polarization …
Accurate estimation of battery parameters such as resistance, capacitance, and open-circuit voltage (OCV) is absolutely crucial for optimizing the performance of lithium-ion batteries and ensuring their safe, reliable operation across numerous applications, ranging from portable electronics to electric vehicles. Here, we …
A multi-scale parameter adaptive method for state of charge and parameter estimation of lithium-ion batteries using dual Kalman filters Energy, 178 ( Jul. 2019 ), pp. 79 - 88, 10.1016/J.ENERGY.2019.04.126
Lithium-sulfur (Li-S) technology was identified as a promising candidate to overcome energy density limitations of common lithium-ion batteries given the world-wide abundance of sulfur as a low-cost alternative to state-of-the-art active materials, such as Ni and Co. Li-S cells have received tremendous recognition in recent years, both from …
Abstract: Accurate parameter identification of a lithium-ion battery is a critical basis in the battery management systems. Based on the analysis of the second-order RC equivalent …
The state-of-charge (SOC) is a fundamental indicator representing the remaining capacity of lithium-ion batteries, which plays an important role in the battery''s optimized operation. In this paper, the model-based SOC estimation strategy is studied for batteries. However, the battery''s model parameters need to be extracted through …
This paper proposes an SOC estimation method for lithium battery, which combines the online parameter identification and an improved particle filter algorithm. ... SOC estimation of lithium battery based on online parameter identification and an improved particle filter algorithm. ... The recursive least square method with forgetting …
To improve the accuracy of Equivalent Circuit Models (ECM) for Electric Vehicles (EV) applications, parameter identification approaches based on Recursive Least Squares (RLS) filters have been proposed. The Variable Forgetting Factor RLS (VFFRLS) algorithms are regarded as one of the most accurate parameter identification methods for lithium-ion …
square algorithm ISSN 1755-4535 Received on 20th December 2019 Revised 15th May 2020 Accepted on 21st May 2020 E-First on 2nd July 2020 ... 3 Parameter identification algorithm for a lithium-ion battery The parameter identification algorithm includes the following variables, which are defined as follows: k is a sampling instant, ...
A Novel Method for Lithium-Ion Battery Online Parameter Identification Based on Variable Forgetting Factor Recursive Least Squares @article{Lao2018ANM, title={A Novel Method for Lithium-Ion Battery Online Parameter Identification Based on Variable Forgetting Factor Recursive Least Squares}, author={Zizhou Lao and Bizhong …
Battery as energy storage equipment plays an important role in social life and industrial production. Lithium-ion batteries have already been widely used in different power demand occasions because of excellent performance. The battery management system (BMS) is the critical part of lithium-ion battery applications. Accurately estimating battery status is the …
For safe and durable operation, the working current and voltage of lithium-ion batteries must be restricted in a window [1], and the battery power (positive for discharging and negative for charging) will be limited by the minimum value of the two restrictions, e.g., (10) {S O P d i s c h arg e = min [S O P d i s c h arg e V S O P d i s c h …
With the popularity of electric vehicles, lithium-ion batteries as a power source are an important part of electric vehicles, and online identification of equivalent circuit model parameters of a lithium-ion battery has gradually become a focus of research. A second-order RC equivalent circuit model of a lithium-ion battery cell is …
In a previous work [], the battery was modeled by the Thevenin model, and the online parameter identification of the battery was realized by forgetting factor recursive least squares (FFRLS).A joint …
4 · The increasing adoption of batteries in a variety of applications has highlighted the necessity of accurate parameter identification and effective modeling, especially for …
To accurately identify the parameters of the lithium battery equivalent circuit model online, this paper proposes a variable forgetting factor recursive least …
Online identification of lithium-ion battery parameters based on an improved equivalent-circuit model and its implementation on battery state-of-power prediction ... Improved splice-electrochemical circuit polarization modeling and optimized dynamic functional multi-innovation least square parameter identification for lithium-ion …
Parameter identification method for lithium-ion batteries based on recursive least square with sliding window difference forgetting factor J. Energy Storage, vol. 44 ( 2021 ), Article 103485, 10.1016/J.EST.2021.103485
The square ternary lithium-ion battery (40 A·h/3.7 V) produced by a company in Jiangsu Province, China, was selected for this study. The main parameters of the battery are listed in Table 1 . To simulate the (dis)charge current, the Neware battery performance tester was used to apply current–time damping to the battery.
This paper establishes the second-order RC circuit model of lithium battery based on the characteristics of lithium battery, and verifies the traditional RLS and LS with Multi-innovation lengths under the HPPC experimental conditions and NEDC cyclic conditions, and reveals the accuracy and convergence of system parameter identification …
The selection of the lithium-ion battery equivalent model and the identification of battery state parameters are the focus of its research field. The battery parameter identification includes two methods, offline and online. Offline recognition is not only a time-consuming process, but also produces insufficiently accurate results. In order to achieve accurate …
Therefore, the parameters of the battery model should continuously change with various factors in the actual operation process. 3.1 Forgetting factor recursive least square algorithm. FFRLS is one of the commonly used online parameter identification algorithms for lithium-ion battery models.
Kai, W.: State of charge (SOC) estimation of lithium-ion battery based on adaptive square root unscented Kalman filter. Int. J. Electromag. Sci. 15, 9499–9516 (2020) Article Google Scholar Rui, Z.: Lithium-ion battery modeling and parameter identification based on decentralized least squares method. J. Mech. Eng.
To verify the proposed algorithm for battery model parameter identification and SoH estimation, we conduct battery tests on the battery test platform. The platform consists of a charge/discharge tester (Arbin BT2000), a programmable constant temperature and humidity chamber (KOMEG KMT-150G), and a computer to record data, as shown in …
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