Jul 2026· 2026 International Conference on Computing, Intelligence, and Applications (CIACON)· pp. 1-6· 0 citations· 16 references
Abstract
Lithium-ion batteries (LiBs) are most favored storage systems used extensively in electric cars (EVs), energy storage systems for renewables, and mobile phones, providing high energy density, high capacity, and efficiency. Accurate State of Charge (SoC) estimation is essential for the effective operation of Battery Management Systems(BMS). To prevent overcharging, over-discharging, and thermal runaway while maximizing performance and lifespan. In this study, the 2RC Equivalent Circuit Model(ECM) is simulated in MATLAB to generate battery data. The 2RC model includes a source for open-circuit voltage (OCV), a series resistance, and two resistor-capacitor networks, which demonstrate how lithium batteries behave during quick changes and stable situations. Calculate the SoC using EKF, AEKF, and AH methods. Comparing the accuracy of these methods shows that AH provides the best results. This simulated data is used to train and evaluate a KAN-based SoC estimation framework. Voltage, current, and temperature responses from the circuit model serve as the input, and the SoC as the target feature for a KAN model. The proposed KAN-based model estimates the SoC accurately, compared with the neural network model.
Improving the performance and lifespan of lithium-ion batteries is a key challenge for the development of electric vehicles. However, accurately estimating the state of charge (SoC), state of health (SoH), and life cycle remains complex due to the electrical, thermal, and aging phenomena associated with these energy st...
Abdel-Hamid Mahamat Ali, Luc Vivien Assiene Mouodo, Paune Félix et al.· Applied Sciences· 0 citations
Lithium-ion batteries are the backbone of electric vehicles, renewable energy storage, and new emerging smart grid applications. However, the safety and the economic value of such batteries depend heavily on the proper assessment of State of Health (SOH). Conventional invasive measurements provide detailed information;...
Jun-Qi Zhang, R. Diao· Journal of Environmental &am...· 0 citations
Accurate estimation of the state of health (SOH) of lithium-ion batteries is essential for ensuring the safety, reliability, and longevity of electric vehicles, battery energy storage systems, and other energy applications. This paper presents a comprehensive review of capacity-based SOH estimation algorithms, focusing...
Manh-Kien Tran, Kintak Raymond Yu, D. MacNeil· Batteries· 0 citations
Voltage mismatch in lithium-ion battery packs is a critical issue that influences the efficiency of the system, safety, and the life cycle in general. Traditional balancing methods, especially passive ones, are associated with the loss of energy and poor flexibility in dynamic operating environments. To overcome these...
S. Gambhire, Sunil Hade, Gopal S. Gawande et al.· International Conference on...· 0 citations
The ever-growing demand for an efficient, reliable and secure electric vehicle has increased the computational requirement for Battery Management System (BMS) for Lithium Iron Phosphate (LiFePO₄) battery technology. This paper presents an approach to systematically analyze the computational requirements of the key para...
Neelima Dudhe, Z. J.Khan· International journal of com...· 0 citations
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