Lithium-ion batteries, as a typical energy storage device, have broad application prospects. However, developing lithium-ion batteries with high energy density, high power density, long lifespan, and safety and reliability remains a huge challenge. Machine learning, as an emerging artificial intelligence technology, has successfully …
Lithium batteries are susceptible to time-varying environmental temperatures, complex electrochemical reactions, ... A hierarchical adaptive extended Kalman filter algorithm for …
Accurate state-of-health (SOH) prediction of lithium-ion batteries (LIBs) plays an important role in improving the performance and assuring the safe operation of the battery energy storage system (BESS). Deep extreme learning machine (DELM) optimized by the ...
The lithium-ion batteries are commonly used in electric vehicle (EV) applications due to their better performances as compared with other batteries. However, lithium-ion battery has some drawbacks such as the overcharged cell which has a risk of explosion, the undercharged cell eventually reduces the life cycle of the battery, and …
The validity and accuracy of the application of AFSA-BP algorithm in SOC estimation of power lithium battery are verified. In the AFSA-BP algorithm, the biggest time frequency is the update of bulletin board.
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 …
This paper presents a battery charge equalization algorithm for lithium-ion battery in electric vehicle (EV) applications. Presently, EV attracts the people interests to be developed and utilized as it fully uses the electric energy from the battery pack to drive the vehicle motor and operate the accessories due to reduction of carbon and greenhouse …
In the energy crisis and post-epidemic era, the new energy industry is thriving, encompassing new energy vehicles exclusively powered by lithium-ion batteries. Within the battery management system of these new energy vehicles, the state of charge (SOC) estimation plays a pivotal role. The SOC represents the current state of charge of …
SOE refers to the remaining available energy of the lithium battery, reflecting the energy that can be released from the lithium battery. SOE is an important …
A Review of Lithium-Ion Battery for Electric Vehicle ...
This paper investigates the problem of modeling lithium-ion batteries based on linear variable parameter (LPV) models. In the modeling framework of LPV, a recursive algorithm that can predict the output voltage of lithium batteries online is proposed. The primary focal point of this research is to propose a model structure that describes all the internal and …
In these applications, battery management systems (BMSs) play the essential role of monitoring and regulating the operational status of the Li-ion batteries for improved performance, life, and safety [[1], [2]]. A wealth of research of advanced BMS algorithms has
In recent years, the modeling and simulation of lithium-ion batteries have garnered attention due to the rising demand for reliable energy storage. Accurate charge cycle predictions are fundamental for optimizing battery performance and lifespan. This study compares particle swarm optimization (PSO) and grey wolf optimization (GWO) …
The state of charge (SOC) of lithium batteries is an important parameter of battery management systems. We aim at the problem that the noise variance is fixed during the estimation of the battery state by the unscented Kalman filter …
Using the 48 V, 50 Ah lithium iron phosphate (LiFePO4) power battery as experimental object, through the periodic charging and …
The work in [] reviewed the application of intelligent algorithms for battery technology in electric vehicles and evaluated the functions, structure, …
This paper explores the practical applications, challenges, and emerging trends of employing Machine Learning in lithium-ion battery research. Delves into …
16. Zhang S, Sun H, Lyu C. A method of SOC estimation for power Li-ion batteries based on equivalent circuit model and extended Kalman filter. In: Proceedings of 13th IEEE Conference on Industrial Electronics …
In Eq. (1), T refers to the battery surface temperature and V is the terminal voltage. Owing to the samples in discrete form, the continued expression should be transferred into discrete expression as below, (2) D T V (k) = T v (k) − T v (k − 1) V (k) − V (k − 1) where V(k) is the terminal voltage at the k th step sample and T v(k) refers to the …
Based on the least-square genetic algorithm, Yang et al. [17] developed a simplified fractional order impedance model for Li-ion batteries and the corresponding parameter identification method. Cao et al. [ 18 ] proposed HEMA method, embedded GA into genetic programming (GP), to help modelling the discharge lifetime of battery …
The algorithm can ensure the internal characteristics of lithium-ion power batteries, and, at the same time, after the matching is completed, the number of lithium batteries in each cluster is equal.
A battery RUL prognostic framework of fusion ND–AR model and RPF algorithm is proposed to realize various lithium-ion batteries RUL estimation. The main contribution of this research can be concluded that: (1) based on low computing complexity AR time series model, the "accelerated" nonlinear degradation feature of the battery …
Lithium battery is widely used in recent years. In this paper, an improved battery model combined with the equivalent circuit model and the electrochemical model is established. The main efforts of our study are: Firstly, the Ohmic resistance of the battery model is identified online based on the Unscented Kalman Filtering (UKF) algorithm.
Aiming at the problem of parameter change of battery model and difficulty in accurately estimating the state of charge (SOC), this paper takes lithium iron phosphate battery as the research object, and based on the first-order RC equivalent circuit model of battery, dynamically identifies the parameters of the model through the recursive least square …
State-of-charge estimation algorithm for Li-ion batteries using long short-term memory network with Bayesian optimization. In 2022 Second International Conference on Interdisciplinary Cyber...
algorithm research for lithium battery SOC in electric vehicles based on adaptive unscented Kalman ... (LOESS). Then, we apply an adaptive extended Kalman filter (AEKF) and long short-term memory ...
The VLCS algorithm has the potential to improve the design, functionality, and performance of lithium-ion battery systems in a variety of applications, including …
the aim of increasing the model accuracy of lithium-ion batteries (LIBs), this paper presents a ... Based on Complex-Order Beetle Swarm Optimization Algorithm February 2023 Micromachines 14(2):413 ...
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