Donghun Wang, Jonghyun Lee, Minchan Kim, Insoo Lee^*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2025-2040, 2023, DOI:10.32604/iasc.2023.034749

Abstract Lithium-ion batteries are commonly used in electric vehicles, mobile phones, and laptops. These batteries demonstrate several advantages, such as environmental friendliness, high energy density, and long life. However, battery overcharging and overdischarging may occur if the batteries are not monitored continuously. Overcharging causes fire and explosion casualties, and overdischarging causes a reduction in the battery capacity and life. In addition, the internal resistance of such batteries varies depending on their external temperature, electrolyte, cathode material, and other factors; the capacity of the batteries decreases with temperature. In this study, we develop a method for estimating the state of charge (SOC)… More >

M. Premkumar¹, R. Sowmya², S. Sridhar³, C. Kumar⁴, Mohamed Abbas^5,6, Malak S. Alqahtani⁷, Kottakkaran Sooppy Nisar^8,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6289-6306, 2022, DOI:10.32604/cmc.2022.030490

Abstract It is critical to have precise data about Lithium-ion batteries, such as the State-of-Charge (SoC), to maintain a safe and consistent functioning of battery packs in energy storage systems of electric vehicles. Numerous strategies for estimating battery SoC, such as by including the coulomb counting and Kalman filter, have been established. As a result of the differences in parameter values between each cell, when these methods are applied to high-capacity battery packs, it has difficulties sustaining the prediction accuracy of overall cells. As a result of aging, the variation in the parameters of each cell is higher as more time… More >

Areeb Khalid^1,*, Syed Abdul Rahman Kashif¹, Noor Ul Ain¹, Ali Nasir²

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3149-3164, 2022, DOI:10.32604/cmc.2022.029322

Abstract When considering the mechanism of the batteries, the capacity reduction at storage (when not in use) and cycling (during use) and increase of internal resistance is because of degradation in the chemical composition inside the batteries. To optimize battery usage, a battery management system (BMS) is used to estimate possible aging effects while different load profiles are requested from the grid. This is specifically seen in a case when the vehicle is connected to the net (online through BMS). During this process, the BMS chooses the optimized load profiles based on the least aging effects on the battery pack. The… More >

Essam Hendawi^1,*, Sattam Al Otaibi¹, Sherif Zaid^2,3,4, Ayman Hoballah¹, Salah K. ElSayed¹, Nagy I. Elkalashy¹, Yasser Ahmed¹

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1009-1025, 2022, DOI:10.32604/csse.2022.022927

Abstract With the increasing development of EVs, the energy demand from the conventional utility grid increases in proportion. On the other hand, photovoltaic (PV) energy sources can overcome several problems when charging EVs from the utility grid especially in remote areas. This paper presents an effective photovoltaic stand-alone charging station for EV applications. The proposed charging station incorporates PV array, a lithium-ion battery representing the EV battery, and a lead-acid battery representing the energy storage system (ESS). A bidirectional DC-DC converter is employed for charging/discharging the ESS and a unidirectional DC-DC converter is utilized for charging the EV battery. The proposed… More >

Muhammad Haris^1,*, Muhammad Noman Hasan¹ , Abdul Basit², Shiyin Qin¹

Journal of Quantum Computing, Vol.3, No.3, pp. 89-95, 2021, DOI:10.32604/jqc.2021.016390

Abstract This article presents a multilayer hybrid classical-quantum classifier for predicting the lifetime of LiFePO4 batteries using early degradation data. The multilayer approach uses multiple variational quantum circuits in cascade, which allows more parameters to be used as weights in a single run hence increasing accuracy and provides faster cost function convergence for the optimizer. The proposed classifier predicts with an accuracy of 92.8% using data of the first four cycles. The effectiveness of the hybrid classifier is also presented by validating the performance using untrained data with an accuracy of 84%. We also demonstrate that the proposed classifier outperforms traditional… More >

Yuhua Yang^1,2, Ke Xu¹, Bo Zhao¹, Nana Liu¹, Jun Zhou^3,4,*

Journal of Renewable Materials, Vol.9, No.5, pp. 855-865, 2021, DOI:10.32604/jrm.2021.014525

Abstract Traditional carbon layer enwrapping active materials cannot easily realize perfect cladding. Therefore, it still cannot prevent the pulverization of active materials during the course of charging/discharging. In this paper, we utilize natural bacteria to absorb nickel acetate, the active materials Ni₃P nanoparticles are well enwrapped, as a natural organisms surviving for billions of years, their cell walls have a perfect carbon structure, and the cell walls become carbon layer through high annealing temperature. Based on this, the yolk-shell Ni₃P–carbon @ reduced graphene oxides paper is prepared, through a proper annealing temperature, the Ni₃P particles disperse in the inner surface or… More >

Yudong Wang^{1, 2}, Jie Tan^{1, *}, Zhenjie Liu¹, Allah Ditta³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2111-2122, 2020, DOI:10.32604/cmc.2020.011098

Abstract Batteries are often packed together to meet voltage and capability needs. However, due to variations in raw materials, different ages of equipment, and manual operation, there is inconsistency between batteries, which leads to reduced available capacity, variability of resistance, and premature failure. Therefore, it is crucial to pack similar batteries together. The conventional approach to screening batteries is based on their capacity, voltage and internal resistance, which disregards how batteries perform during manufacturing. In the battery discharge process, real time discharge voltage curves (DVCs) are collected as a set of unlabeled time series, which reflect how the battery voltage changes.… More >

Hongwang Zhao^{1, *}, Yuanhua Chen¹, Xiaogang Liu²

FDMP-Fluid Dynamics & Materials Processing, Vol.15, No.4, pp. 293-305, 2019, DOI:10.32604/fdmp.2019.08361

Abstract In order to ensure that the lithium-ion battery pack keeps good working performance during the driving of electric vehicle, the heat generation mechanism and heat transfer characteristics of lithium-ion battery are analyzed. The power battery pack of electric vehicle is simulated by advanced vehicle simulator. The simulation results of battery pack current under typical cycle conditions and the heat source curve of lithium ion battery are obtained, which provide data for the simulation of heat source input of battery temperature field. On this basis, the flow field and temperature fiel d of the original lithium-ion battery pack of electric vehicle… More >