Aug 2026· International Conference on Information Security and Cryptology· pp. 352-357· 0 citations· 15 references
Abstract
Accurate prediction of the State of Charge (SoC) is essential for the efficient operation of electric vehicles through Battery Management Systems. But it is difficult to make accurate SoC estimates for lithium-ion batteries because of their nonlinear chemical nature and dependency on factors like temperature and aging. This study evaluates three different approaches for SoC estimation: Feedforward Neural Network (FNN), XGBoost Regressor, and Extended Kalman Filter (EKF). To do so, the models are trained by employing battery datasets collected under different driving cycles and temperatures. Evaluation of the models is based on errors including Mean Absolute Error (MAE), Mean Square Error (MSE), and Mean Percentage Error (MPE).
The accurate estimation of State of Charge (SoC) is critical for safe, reliable, and optimistic operation of Battery Electric Vehicles (BEVs). Nevertheless, achieving robust SoC estimation is a big challenge because of nonlinear battery dynamics, parameter variability, sensor noise, and uncertain initial conditions. St...
Mazhar Hussain Shaik, Shafiq Ul Rehman, I. Ibrahim· Clean Energy Science and Tec...· 0 citations
For the purpose of assuring the safety, dependability, and prolonged lifespan of energy storage systems in electric vehicles, it is vital to have an accurate estimation of the level of charge of the lithium-ion battery. Attempts to capture the complicated and non-linear behaviors of batteries are frequently unsuccessfu...
S.Kanthalakshmi G.R.Radhika· Lex Localis-journal of Local...· 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
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
The estimation accuracy of the battery state of charge (SOC) directly affects the reliable and stable operation of the battery management system (BMS). In complex operating conditions such as vehicle-mounted applications and energy storage power stations, systematic biases and random noise are common in voltage and cur...
Peng Wang, Shu-Song Wang, Yi Su et al.· World Electric Vehicle Journ...· 0 citations
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