Synthesis and Study of Cathode Materials Based on Carbon Nanotubes for Lithium-Ion Batteries

Concerns over fossil fuel depletion, fluctuating fuel prices, and CO2 emissions have accelerated the development of electric vehicle (EV) technologies. This article reviews advancements in EV fast charging technology and explores the development of battery-assisted DC fast charging stations to address the limitations of traditional chargers. Our proposed approach integrates battery storage, allowing chargers to operate independently of the electric grid by storing electrical energy during off-peak hours and releasing it during peak times. This reduces dependence on grid power and enhances grid stability. Moreover, the transformer-less, modular design of the proposed solution offers greater flexibility, scalability, and reduced installation costs. Additionally, the use of smart energy management systems, incorporating artificial intelligence and machine learning techniques to dynamically adjust charging rates, will be discussed to optimize efficiency and cost-effectiveness.

Section: Battery Cell Typementioning

confidence: 99%

Advancing Electric Vehicle Infrastructure: A Review and Exploration of Battery-Assisted DC Fast Charging Stations

Aksoz,

Asal,

Biçer

et al. 2024

“…Shchegolkov, A.V et al presented a study of the conditions and possibilities for the intercalation of hexafluorophosphate anions into CNT-based electrodes. Electrode materials were obtained at various concentrations of CNT/graphite: CNT-4F, CNT-6, and CNT-6F [17]. Sheem, K et al prepared cathodes of LiCoO 2 with a density of up to 4.0 gcm −3 , fabricated using alternate conducting agents of MWNT and conventional carbon black (Super P).…”

Section: Introductionmentioning

confidence: 99%

Research on the Performance Improvement Method for Lithium-Ion Battery in High-Power Application Scenarios

Zhou,

Zhu,

et al. 2024

With the development of technology, high-power lithium-ion batteries are increasingly moving towards high-speed discharge, long-term continuous output, instantaneous high-rate discharge, and miniaturization, and are being gradually developed towards the fields of electric tools, port machinery and robotics. Improving the power performance of batteries can be achieved from multiple dimensions, such as electrochemical systems and battery design. In order to improve the power performance of lithium-ion batteries, this paper proposes design methods from the perspective of electrochemical systems, which include increasing the high-rate discharge capacity and low impedance of the battery. This article also studies the preparation of high-power lithium-ion batteries. This article aims to improve the rate performance of batteries by studying high-performance cathode materials, excellent conductive networks, and high-performance electrolytes. This article successfully screened high-performance cathode materials by comparing the effects of different particle sizes of cathode materials on electrode conductivity and battery internal resistance. By comparing the effects of electrolyte additives under pulse cycling, high-quality electrolyte additive materials were selected. By comparing the effects of different types, contents, and ratios of conductive agents on electrode conductivity, battery internal resistance, high-quality conductive agents, and appropriate ratios were selected. Finally, a 10 Ah cylindrical high-power lithium-ion battery with a specific energy of 110 Wh/kg, pulse discharge specific power of 11.3 kW/kg, an AC internal resistance of ≤0.7 m Ω, a 10C full capacity discharge cycle of over 1700, a 30C full capacity discharge cycle of over 500, and a continuous discharge capacity of 10C–30C, and a pulse discharge capacity of over 100C was prepared.

“…Lithium batteries, with their significant advantages such as high energy density, ecofriendliness, low self-discharge rate, and long lifespan, have become the preferred choice in emerging energy storage technologies and are widely used across various fields [1][2][3][4][5]. However, the capacity of these batteries gradually diminishes through repeated charging and discharging cycles.…”

Section: Introductionmentioning

confidence: 99%

Predicting the Remaining Useful Life of Lithium-Ion Batteries Using 10 Random Data Points and a Flexible Parallel Neural Network

Jiang,

Huang,

2024

Accurate Remaining Useful Life (RUL) prediction of lithium batteries is crucial for enhancing their performance and extending their lifespan. Existing studies focus on continuous or relatively sparse datasets; however, continuous and complete datasets are rarely available in practical applications due to missing or inaccessible data. This study attempts to achieve the prediction of lithium battery RUL using random sparse data from only 10 data points, aligning more closely with practical industrial scenarios. Furthermore, we introduce the application of a Flexible Parallel Neural Network (FPNN) for the first time in predicting the RUL of lithium batteries. By combining these two approaches, our tests on the MIT dataset show that by randomly downsampling 10 points per cycle from 10 cycles, we can reconstruct new meaningful features and achieve a Mean Absolute Percentage Error (MAPE) of 2.36% in predicting the RUL. When the input data are limited to the first 10 cycles using the dataset constructed from random downsampling and the FPNN, the predicted RUL MAPE is 0.75%. The method proposed in this study offers an accurate, adaptable, and comprehensible new solution for predicting the RUL of lithium batteries, paving a new research path in the field of battery health monitoring.