The monitoring and prognosis of cell degradation in lithium-ion (Li-ion) batteries are essential for assuring the reliability and safety of electric and hybrid vehicles. This paper aims to develop a reliable and accurate model for online, simultaneou...
Accurate state of charge (SOC) estimation is crucial for the safety, reliability, and energy efficiency of lithium-ion battery systems. However, variations in battery parameters and the loss of historical information during the update steps of tradit...
State of Charge (SOC) is essential for a smart Battery Management System (BMS). Traditional SOC estimation methods of lithium-ion batteries are usually conducted using battery equivalent circuit models (ECMs) and the impact of current sensor bias on...
In recent years, electric vehicles (EVs), hybrid electric vehicles (HEVs), and plug-in electric vehicles (PEVs) have become very popular. Therefore, the use of secondary batteries exponentially increased in EV systems. Battery fuel gauges determine t...
The accurate state of charge (SoC) online estimation for lithium-ion batteries is a primary concern for predicting the remaining range in electric vehicles. The Sigma points Kalman Filter is an emerging SoC filtering technology. Firstly, the charge a...
In order to improve the estimation accuracy of the battery state of charge (SOC) based on the equivalent circuit model, a lithium-ion battery SOC estimation method based on adaptive forgetting factor least squares and unscented Kalman filtering is pr...
Accurate modeling of the nonlinear relationship between the open circuit voltage (OCV) and the state of charge (SOC) is required for adaptive SOC estimation during the lithium-ion (Li-ion) battery operation. Online SOC estimation should meet several...
The SOC estimation of UAV lithium batteries plays a crucial role in the mission planning and safe flight of UAVs. Aiming at existing UAV lithium battery SOC estimation problems, such as low estimation accuracy and poor real-time performance, a real-t...
This study describes an online estimation of the model parameters and state of charge (SOC) of lithium iron phosphate batteries in electric vehicles. A widely used SOC estimator is based on the dynamic battery model with predeterminate parameters. Ho...
Accurate estimation of State-of-Charge (SoC) is essential for ensuring the safe and efficient operation of electric vehicles (EVs). Currently, second-order RC equivalent circuit models do not account for the influence of battery charging and discharg...
As a superior solution to the developing demand for energy storage, lithium-ion batteries play an important role in our daily lives. To ensure their safe and efficient usage, battery management systems (BMSs) are often integrated into the battery sys...
State-of-charge (SoC) estimation is one of the core functions of battery energy management systems. An accurate SoC estimation can guarantee the safe and reliable operation of the batteries system. In order to overcome the practical problems of low a...
Kalman filters have shown to be a very accurate and robust method for State of Charge estimation. However, their performance depends heavily on the accuracy of the used battery model and its parameters. These battery model parameters have shown to va...
When a lithium-ion cell’s series resistance is underestimated, the pre-update terminal-voltage innovation contains the first-order term
Battery management is the key technical link for electric vehicles. A good battery management system can realize the balanced charge and discharge of batteries, reducing the capacity degradation and the loss of health caused by battery overcharge and...
To ensure the safe and stable operation of energy storage systems (ESS) during peak power supply periods, this study proposes an enhanced state of charge (SOC) estimation framework for lithium-ion batteries. By integrating an Improved Adaptive Forget...
State of charge (SOC) estimation is generally acknowledged to be one of the most important functions of the battery management system (BMS) and is thus widely studied in academia and industry. Based on an accurate SOC estimation, the BMS can optimize...
The accurate estimation of the state of charge (SOC) plays a crucial role in ensuring the range of electric vehicles (EVs) and the reliability of the EVs battery. However, due to the dynamic working conditions in the implementation of EVs and the lim...
For model-based state of charge (SOC) estimation methods, the battery model parameters change with temperature, SOC, and so forth, causing the estimation error to increase. Constantly updating model parameters during battery operation, also known as...
State of charge (SOC) estimation is the core of any battery management system. Most closed-loop SOC estimation algorithms are based on the equivalent circuit model with fixed parameters. However, the parameters of the equivalent circuit model will ch...
The accurate estimation of a lithium-ion battery’s state of charge (SOC) plays an important role in the operational safety and driving mileage improvement of electrical vehicles (EVs). The Adaptive Extended Kalman filter (AEKF) estimator is com...
The accurate monitoring of state of charge (SOC) and state of health (SOH) is critical for the reliable management of lithium-ion battery (LIB) systems. In this paper, online model identification is scrutinized to realize high modeling accuracy and r...
Due to its accuracy, simplicity, and other advantages, the Kalman filter method is one of the common algorithms to estimate the state-of-charge (SOC) of batteries. However, this method still has its shortcomings. The Kalman filter method is an algori...
In order to improve the estimation accuracy of the state of charge (SOC) of electric vehicle power batteries, a dual Kalman filter method based on the online identification of model parameters is proposed to estimate the state of charge in lithium-io...
Online state-of-charge (SOC) estimation for lithium-ion batteries is one of the most important tasks of the battery management system in ensuring its operation safety and reliability. Due to the advantages of learning the long-term dependencies in be...
Accurate state-of-charge (SOC) estimation is essential for range prediction, power allocation, and operational safety in electric vehicles. Low-temperature operation introduces coupled effects of capacity degradation and polarization dynamics, which...
Accurate online parameter identification and state-of-charge (SOC) estimation are essential for lithium-ion battery management systems. However, under constant or quasi-constant current operating conditions, the system excitation is inherently weak,...
Accurately estimating the online state-of-charge (SOC) of the battery is one of the crucial issues of the battery management system. In this paper, the gas–liquid dynamics (GLD) battery model with direct temperature input is selected to model Li(NiMn...
State of charge (SOC) and state of health (SOH) are two significant state parameters for the lithium ion batteries (LiBs). In obtaining these states, the capacity of the battery is an indispensable parameter that is hard to detect directly online. Ho...
The precise estimation of the state of charge (SOC) in lithium batteries is crucial for enhancing their operational lifespan. To address the issue of reduced accuracy in SOC estimation caused by the random missing values of lithium battery current me...
The lithium-ion battery is a viable power source for hybrid electric vehicles (HEVs) and, more recently, electric vehicles (EVs). Its performance, especially in terms of state of charge (SOC), plays a significant role in the energy management of thes...
Due to its advantages of high voltage level, high specific energy, low self-discharging rate and relatively longer cycling life, the lithium-ion battery has been widely used in electric vehicles. To ensure safety and reduce degradation during the lit...
An accurate state-of-charge (SOC) can not only provide a safe and reliable guarantee for the entirety of equipment but also extend the service life of the battery pack. Given that the chemical reaction inside the lithium-ion battery is a highly nonli...
State of charge (SOC) estimation is the core algorithm of the battery management system. However, the commonly used model-based, data-driven, or experiment-based methods struggle to independently achieve accurate SOC estimation under different workin...
With an accurate state of charge (SOC) estimation, lithium-ion batteries (LIBs) can be protected from overcharge, deep discharge, and thermal runaway. However, selecting appropriate algorithms to maintain the trade-off between accuracy and computatio...
A new optimization method for estimating the State of Charge (SOC) of battery charge state is proposed. This method incorporates the Levenberg–Marquardt Algorithm (LMA) for online parameter identification and the Extended Kalman Filter (EKF) fo...
In order to improve the estimation accuracy of the state of charge (SOC) of lithium iron phosphate power batteries for vehicles, this paper studies the prominent hysteresis phenomenon in the relationship between the state of charge and the open circu...
With the increase in the amount of actual operating data on electric vehicles, how to analyze and process useful information from existing battery charging and discharging data and apply it to subsequent state estimation is worthy of in-depth thinkin...
Many battery state of charge (SOC) estimation methods have been studied for decades; however, it is still difficult to precisely estimate SOC because it is nonlinear and affected by many factors, including the battery state and charge–discharge...
The precise estimation of the state of charge (SOC) is fundamental to the reliable operation of lithium-ion batteries. The development of deep learning techniques makes it possible to employ advanced methods to estimate a battery’s SOC. In orde...
The state-of-charge (SOC) is a fundamental indicator representing the remaining capacity of lithium-ion batteries, which plays an important role in the battery’s optimized operation. In this paper, the model-based SOC estimation strategy is stu...
In a battery management system, the accurate estimation of the battery’s state of health (SOH) and state of capacity (SOC) are vital functions. The traditional estimation methods have limitations. To accurately estimate the SOC and SOH of power...
This paper presents a method to validate state of charge (SOC) estimations in batteries for their use in remotely manned aerial vehicles (UAVs). The SOC estimation must provide the mission control with a measure of the available range of the aircraft...
This paper presents a method for use in estimating the state of charge (SOC) of lithium-ion batteries which is based on an electrochemical impedance equivalent circuit model with a controlled source. Considering that the open-circuit voltage of a bat...
The model parameters of the lithium-ion battery are of great importance to model-based battery state estimation methods. The fact that parameters change in different rates with operation temperature, state of charge (SOC), state of health (SOH) and o...
Open circuit voltage (OCV) is crucial for battery degradation analysis. However, high-precision OCV is usually obtained offline. To this end, this paper proposes a novel self-evaluation criterion based on the capacity difference of State of Charge (S...
An accurate state of charge (SOC) estimation of the on-board lithium-ion battery is of paramount importance for the efficient and reliable operation of electric vehicles (EVs). Aiming to improve the accuracy and reliability of battery SOC estimation,...
Accurate state of charge (SOC) estimation is essential for reliable battery management systems operating over a wide temperature range. This study proposes a joint estimation framework that combines a temperature-matched dual open-circuit-voltage (OC...
The state of charge (SOC) of a lithium-ion battery plays a key role in ensuring the charge and discharge energy control strategy, and SOC estimation is the core part of the battery management system for safe and efficient driving of electric vehicles...
The state of charge (SOC) and the state of health (SOH) are the two most important indexes of batteries. However, they are not measurable with transducers and must be estimated with mathematical algorithms. A precise model and accurate available batt...
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