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14 articles for “State of Charge Estimation”
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Particle Swarm Optimization Framework for Accurate Battery State-of-Charge and Remaining Useful Life Estimation
Abstract: Accurate estimation of the State of Charge (SOC) and State of Health (SOH) of a battery is key to safe and efficient management of batteries in electric vehicles and energy-storage systems. However, it is challenging due to high nonlinearity, varying operating conditions, measurement noise, and limited access to comprehensive electrochemical parameters. Traditional data-driven models often generalize poorly and require heavy tuning, which can produce unstable predictions. To address these problems, …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 53–64 Read article
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Multimodal Data Fusion with Hybrid Machine Learning for Enhanced Prediction of Li-Ion Battery Remaining Useful Life and State of Charge
Abstract: Lithium-ion battery materials used in modern energy storage systems are required to exhibit high reliability, safety, and long lifecycle performance under varying operational and environmental conditions. Accurate prediction of Remaining Useful Life (RUL) and State of Charge (SoC) is therefore essential for understanding material degradation behavior, improving manufacturing quality, and enabling effective lifecycle management. However, nonlinear electrochemical aging, load variability, and thermal uncertainty significantly complicate accurate estimation of these parameters. …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
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Modelling and Performance Evaluation of a Multiport Converter for Active Balancing of Lithium- ion Battery Cells
Abstract: In this paper, a flexible multiport DC-DC converter-based active cell balancing technique for Li-ion battery packs is presented. Cell balancing plays an important role in terms of safety, capacity utilization, and battery lifespan. For Li-ion cells in series configuration, the difference in voltages and states of charge (SOCs) leads to imbalance issues which might negatively affect their performance and shorten their lifespan. To solve these problems, the proposed technique utilizes …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 2, 2026 Read article
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Optimized Machine Learning Framework for Battery State Prediction in Smart Charging Systems
Abstract: Good estimation of battery states, including State-of-Charge (SoC), State-of-Health (SoH), and Remaining Useful Life (RUL), are important in managing energy wisely and controlling the adaptive charging. This work introduces a streamlined machine learning model based on the ability to use multi-dimensional sensor measurements in terms of voltage, current, temperature, and cycle number to forecast battery conditions with high accuracy. Decent preprocessing, such as noise elimination, feature scaling, and calculated features, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 11–23 Read article
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History and Applications of Kalman Filter: A Review
Abstract: The Kalman filter is a powerful algorithm that is used to estimate the dynamic system states with noisy measurements and uncertain behaviors. It is an optimal estimator that minimizes the average squared error between the estimated states and the true states, given the noisy data and a model of the system. The recursive algorithm is highly effective in tracking and predicting the state of complex systems over time. Kalman filters …
Published in International Journal of Electrical Power and Machine Systems · Vol. 2, Issue 1, 2024 · pp. 14–23 Read article
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Fast-Charging Techniques for Electric Vehicle Batteries
Abstract: EVs (Electric Vehicles) are becoming the popular mode of green transport, boosted by their efficiency, lower emission and technological vibrancy. But slow battery charging still poses one of the primary stumbling blocks to EV deployment. Conventional charging methods that take hours necessitate inconvenience and range- anxiety. To tackle this, scientists and companies are in a race to develop fast-changing technologies that can charge batteries within minutes without compromising safety. These …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 4, Issue 1, 2026 · pp. 1–8 Read article
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Analyzing And Predicting the Battery Health of Battery Energy in EV’s
Abstract: The most widely used energy storage components in products like electric cars, portable electronics, and energy storage systems are lithium batteries. On the other hand, if lithium batteries are not regularly checked, they may perform worse, have a shorter lifespan, or even explode or cause serious harm. Our proposal is to develop a state of health monitoring system for lithium batteries and an algorithm for estimating the state of charge …
Published in Journal of Nuclear Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 28–37 Read article
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Development of a Polymer-Encapsulated IoT-Based Sensor for Thermal and Electrical Protection of EV Batteries
Abstract: Electric Vehicles (EVs) mark a critical shift toward sustainable transportation, with Battery Management Systems (BMS) playing a vital role in ensuring battery safety, reliability, and efficiency. The proposed BMS in this project incorporates real-time charge monitoring, temperature sensing, and fire detection capabilities to address safety concerns associated with lithium-ion batteries. Key features include current and voltage tracking, State of Charge (SoC) estimation, fault detection, and a user-friendly LCD interface. By …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 582–591 Read article
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Review of Battery Management System and SOC
Abstract: The perception of electric cars (EVs) as a strong alternative to for internal combustion engine automobiles is growing. For electric vehicle (EV) technologies to advance, they must develop quickly, especially in the area of battery technology. light weight, increased energy capacity, quick charging times, lithium-ion (Li-ion) batteries are generally used for electric vehicles (EVs). The efficiency of the battery management system (BMS) and battery performance are critical elements influencing electric …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 1, 2026 · pp. 08–16 Read article
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Management of Lead–Acid Battery System in Electric Vehicles
Abstract: To determine the lead-acid battery's state of charge in electric vehicles, a novel coulometric method is presented in this article. There are two major problems with the main state of charge algorithms that are currently in use: one defines the state of charge incorrectly for applications involving electric vehicles, and the other uses the accumulator's static performance sub-optimally to estimate its state under dynamic stresses. To address these two shortcomings, …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 1, 2024 · pp. 18–27 Read article
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Theoretical Study of Z = 122 Nuclei
Abstract: We used atomic nuclei with proton number Z = 122 to calculate bulk properties within the relativistic mean field (RMF) theory. We utilized the force parameters recognized as NL3 in our calculations. We extend our calculation to isotopic series of Z = 122 and analyses the theoretical outcomes. A whole isotopic chain of nuclei with atomic number 𝑍 = 122 Z=122 is included in our inquiry, enabling a methodical examination …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 1–9 Read article
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Battery Management System (BMS)
Abstract: This review of the literature delves into the changes, structure, and the latest BMS (Battery Management Systems) technologies implemented in electric vehicles, smart grids, and energy storage, respectively. The studies emphasize the need for accurate battery modeling, advanced estimation algorithms, robust hardware design, and safety regulations. The research describes how contemporary BMSs perform integration of modeling, monitoring, control, cell balancing, and diagnostics in order to facilitate safe and energy- efficient …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 32–43 Read article
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IoT-Based Battery Health Monitoring for Electric Vehicles Using Machine Learning
Abstract: With increasing utilization of the Electric Vehicles (EV)s in global scale, battery health management becomes a critical factor which has great impact on vehicle performance, safety and longevity. Battery materials, such as NMC LFP lithium-ion batteries and lithium-ion batteries, degrade over time from charging behaviour, heat stress, discharging voltage profiles and environmental limits. Conventional BMS only offer threshold based health diagnostics and cannot perform accurate degradation prediction. This work presents …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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Optimizing Power Generation from Building Ventilation Systems: A Study on Exhaust Fan Efficiency
Abstract: Due to population growth, the world's energy consumption has increased dramatically in both wealthy and developing nations in recent years, and by 2042, it is predicted to have doubled or more. Since a few years ago, the use of innovative sustainable power sources to meet energy demands has been gradually increasing. We've chipped away at a different idea because of this. As an alternative energy source, renewable energy (RE) resources …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 2, 2023 · pp. 22–27 Read article