相关论文: A virtual sensor fusion approach for state of char…

This paper investigates the observability of one of the most commonly used equivalent circuit models (ECMs) for lithium-ion batteries and presents a method to estimate the state of charge (SOC) in the presence of sensor biases, highlighting…

This paper addresses state of charge (SOC) estimation for lithium iron phosphate (LFP) batteries, where the relatively flat open-circuit voltage (OCV-SOC) characteristic reduces observability. A residual bias compensation dual extended…

Accurate estimation of the state of charge (SOC) and state of health (SOH) is crucial for the safe and reliable operation of batteries. Voltage measurement bias highly affects state estimation accuracy, especially in Lithium Iron Phosphate…

Robust and Real-time State of Charge (SOC) estimation is essential for Lithium Iron Phosphate (LFP) batteries, which are widely used in electric vehicles (EVs) and energy storage systems due to safety and longevity. However, the flat Open…

This paper presents findings on dynamic cell modeling for state-of-charge (SOC) estimation in an autonomous electric vehicle (AEV). The studied cells are Lithium-Ion Polymer-based with a nominal capacity of around 8Ah, optimized for…

This article presents a novel empirical study for the estimation of the State of Charge (SOC) of a lithium-ion (Li-ion) battery which uses a deep learning model with three hidden layers. We model a series of ten vehicle drive cycles that…

For the battery management system of electric vehicle, accurate estimation of the State of Charge of Lithium-ion battery can effectively avoid structural damage caused by overcharge or over discharge inside the battery. Considering that the…

Accurate and computationally light algorithms for estimating the State of Charge (SoC) of a battery's cells are crucial for effective battery management on embedded systems. In this letter, we propose an Adaptive Extended Kalman Filter…

Knowledge of remaining battery charge is fundamental to electric vehicle deployment. Accurate measurements of state-of-charge (SOC) cannot be directly obtained, and estimation methods must be used instead. This requires both a good model of…

This manuscript presents an algorithm for individual Lithium-ion (Li-ion) battery cell state of charge (SOC) estimation when multiple cells are connected in parallel, using only terminal voltage and total current measurements. For battery…

LiFePO4 batteries are widely used in electric vehicles and energy storage systems due to long cycle life and high safety performance. However, the OCV-SOC curve (OSC) of these batteries features a long plateau region, making state of charge…

Accurate state of charge (SOC) estimation is critical for ensuring the safety, reliability, and efficiency of lithium-ion batteries in electric vehicles and energy storage systems. Electrochemical models provide high fidelity for SOC…

The future evolution of technological systems dedicated to improve energy efficiency will strongly depend on effective and reliable Energy Storage Systems, as key components for Smart Grids, microgrids and electric mobility. Besides…

This paper presents a novel framework for state-of-charge estimation of rechargeable batteries in electric vehicles using a two-stage nonlinear estimator called the eXogenous Kalman filter (XKF). The nonlinear estimator consists of a…

Li-ion batteries are essential for the energy supply of satellites. The accurate estimation of their states is important for the reliable and safe operation in space. This paper introduces a new algorithm for the estimation of SOC and SOH.…

We proposed a new estimation algorithm of extended Kalman filter (EKF) based on improved Thevenin model; Experiments were carried out to verify the validity with seven 4Ah lithium cobalt acid batteries in series. The experimental results…

Motion estimation approaches typically employ sensor fusion techniques, such as the Kalman Filter, to handle individual sensor failures. More recently, deep learning-based fusion approaches have been proposed, increasing the performance and…

This paper proposes a way to augment the existing machine learning algorithm applied to state-of-charge estimation by introducing a form of pulse injection to the running battery cells. It is believed that the information contained in the…

The state of charge (SOC) of lithium-ion batteries needs to be accurately estimated for safety and reliability purposes. For battery packs made of a large number of cells, it is not always feasible to design one SOC estimator per cell due…

Considering the expanding useofembedded devices equipped with rechargeable batteries, especially Li-ionbatteries that have higher power and energy density, the battery management systemis becomingincreasingly important. Infact,…