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Relevant bibliographies by topics / State of Charge (SoC) Monitoring

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Academic literature on the topic 'State of Charge (SoC) Monitoring'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "State of Charge (SoC) Monitoring"

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M., Surendar, and Pradeepa P. "Future Challenges in State of Charge Estimation for Lithium-Ion Batteries." International Journal of Engineering and Advanced Technology (IJEAT) 10, no. 1 (2020): 215–23. https://doi.org/10.35940/ijeat.A1789.1010120.

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Energy storage system is an Emerging technology in past few decades. The Energy storage system is an important technology for Electric Vehicles, Hybrid Electric Vehicles (EV) and (HVE) and Micro grid system. The Battery Management System (BMS) is need to be control and monitor the various parameter of the battery such as SOC , SOH, C-Rate, E-Rate ,Temperature , RVL , EOL and so on. However, the (SOC) State of Charge is an important estimation for the online control and BMS monitoring. The SOC is the challenging task when online control and BMS monitoring. This various technique or methods avai

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Dou, Zhaoliang, Jiaxin Li, Hongjuan Yan, Chunlin Zhang, and Fengbin Liu. "Real-Time Online Estimation Technology and Implementation of State of Charge State of Uncrewed Aerial Vehicle Lithium Battery." Energies 17, no. 4 (2024): 803. http://dx.doi.org/10.3390/en17040803.

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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-time online estimation scheme for UAV lithium battery SOC is proposed. A model-based approach is adopted to establish an SOC estimation model on the basis of the Thevenin equivalent circuit model, and a UAV lithium battery online monitoring device is developed to monitor the current and voltage of the UAV lithium battery in real time and import the

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Bawango, Kesya Maria Magdalena, Hesky S. Kolibu, and Seni H. J. Tongkukut. "Estimasi State of Charge Pada Baterai Li-ion Dengan Menggunakan Metode Coulomb Counting." JURNAL LPPM BIDANG SAINS DAN TEKNOLOGI 9, no. 2 (2024): 78–84. https://doi.org/10.35801/jlppmsains.9.2.2024.51598.

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Baterai berfungsi sebagai tempat penyimpanan energi yang dihasilkan dari sumber energi dan dapat digunakan untuk menyuplai energi saat sumber energi utama tidak tersedia. Dengan demikian, baterai memungkinkan penyimpanan energi dan penggunaannya dalam waktu yang fleksibel. Monitoring baterai diperlukan agar performa baterai dapat mencapai maksimal. Salah satu aspek monitoring baterai adalah mengestimasi state of charge (SOC). Penelitian ini melibatkan empat merek baterai Li-ion yang berbeda, dengan pengambilan data arus dan tegangan selama proses pengosongan baterai dilakukan selama 60 menit d

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Rybalchenko, Maria, Nathan Quill, D. Noel Buckley, and Robert P. Lynch. "(Invited) State of Charge Monitoring of Vanadium Flow Batteries Using Spectroscopic and Electrochemical Methods." ECS Meeting Abstracts MA2022-02, no. 30 (2022): 1101. http://dx.doi.org/10.1149/ma2022-02301101mtgabs.

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Vanadium Flow Batteries (VFBs) are a promising energy storage technology, particularly for large and medium scale applications. In a VFB, energy is stored in two vanadium electrolytes separated by a nafion membrane. The use of vanadium electrolytes in both half-cells minimises cross contamination issues which have plagued other flow battery chemistries. The electrodes, electrolytes and membrane are key areas of research for VFBs with the aim of improving efficiency, energy density and costs. Accurately monitoring state-of-charge (SoC) is vital for any rechargeable battery system. It is importa

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Dyartanti, Endah Retno, Anif Jamaluddin, Muhammad Farrel Akshya, et al. "The State of Charge Estimation of LiFePO4 Batteries Performance Using Feed Forward Neural Network Model." Applied Mechanics and Materials 918 (January 9, 2024): 85–94. http://dx.doi.org/10.4028/p-iidzs6.

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Lithium-ion batteries like LiFePO4 become a new choice for electrical energy sources in the world and can be used on electric vehicles. Battery packs monitoring by Battery Management System in electric vehicles require accurate monitoring. The inaccuracy of monitoring such property can lead to low safety, low efficiency and battery’s life reduction. Estimating state of charge (SoC) to prevent battery damage from overcharging and over discharging. Some of the methods used to estimate SoC such as Coulomb Counting have errors during the charge and discharge process. This research proposes a count

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Kurzweil, Peter, Bernhard Frenzel, and Wolfgang Scheuerpflug. "A Novel Evaluation Criterion for the Rapid Estimation of the Overcharge and Deep Discharge of Lithium-Ion Batteries Using Differential Capacity." Batteries 8, no. 8 (2022): 86. http://dx.doi.org/10.3390/batteries8080086.

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Differential capacity dQ/dU (capacitance) can be used for the instant diagnosis of battery performance in common constant current applications. A novel criterion allows state-of-charge (SOC) and state-of-health (SOH) monitoring of lithium-ion batteries during cycling. Peak values indicate impeding overcharge or deep discharge, while dSOC/dU = dU/dSOC = 1 is close to “full charge” or “empty” and can be used as a marker for SOC = 1 (and SOC = 0) at the instantaneous SOH of the aging battery. Instructions for simple state-of-charge control and fault diagnosis are given.

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Ma, Jinkai, Haodong Yan, Yitian Sun, et al. "Comparison and Evaluation of State-of-charge and Health Monitoring Methods for Lithium-sulfur Batteries." International Journal of Energy 5, no. 1 (2024): 5–14. http://dx.doi.org/10.54097/mhpg6x76.

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State-of-charge (SOC) estimation and state-of-health (SOH) prediction of lithium-sulfur batteries is an extremely important technology for battery management systems (BMS), which is affected by factors such as internal chemical reactions and external temperature changes of lithium-sulfur batteries, which makes it difficult to predict the state of charge and state of health of lithium-sulfur batteries. Firstly, the retrieval status of battery SOC estimation and SOH prediction is introduced, then the main methods and advantages and disadvantages of various methods are introduced, and finally the

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Afrida, Yenni, Jeckson J, and Ubaidah U. "Studi Penentuan State Of Charge (SOC) pada Baterai Valve Regulated Lead Acid NP7-12 Menggunakan MATLAB." Electrician : Jurnal Rekayasa dan Teknologi Elektro 17, no. 2 (2023): 146–50. http://dx.doi.org/10.23960/elc.v17n2.2481.

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Abstract — To maintain battery performance, it is necessary to have a battery monitoring system that functions to determine several parameters in the battery, such as voltage, current, capacitance and battery capacity. The technology for knowing battery capacity is often known as state of charge (SOC). State of charge (SOC) is the ratio of the remaining energy to the maximum energy capacity of the battery. State of charge values are often expressed in percentage form, 0 percent -100 percent. Estimating the value of the state of charge is quite important in battery monitoring technology. The

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Syafii, Syafii, Irfan El Fakhri, Thoriq Kurnia Agung, and Farah Azizah. "Design of battery state of charge monitoring and control system using coulomb counting method based." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 2 (2024): 736. http://dx.doi.org/10.11591/ijeecs.v33.i2.pp736-745.

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<span>Lead-acid batteries are commonly used in photovoltaic systems to store solar energy for continuous use. However, lead-acid batteries have a relatively short lifespan due to frequent over-charging and over-discharging. A battery management system (BMS) is essential for accurately predicting the battery state of charge (SoC) value in order to extend the battery lifespan. In this research, a BMS is developed using the coulomb counting method to estimate the SoC value of a lead-acid battery. The coulomb counting algorithm provides a reliable estimation of the battery’s SoC value by cal

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Syafii, Irfan El Fakhri, Thoriq Kurnia Agung, and Farah Azizah. "Design of battery state of charge monitoring and control system using coulomb counting method based." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 2 (2024): 736–45. https://doi.org/10.11591/ijeecs.v33.i2.pp736-745.

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Lead-acid batteries are commonly used in photovoltaic systems to store solar energy for continuous use. However, lead-acid batteries have a relatively short lifespan due to frequent over-charging and over-discharging. A battery management system (BMS) is essential for accurately predicting the battery state of charge (SoC) value in order to extend the battery lifespan. In this research, a BMS is developed using the coulomb counting method to estimate the SoC value of a lead-acid battery. The coulomb counting algorithm provides a reliable estimation of the battery’s SoC value by calculati

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Dissertations / Theses on the topic "State of Charge (SoC) Monitoring"

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Fairweather, Andrew James. "State-of-Health (SoH) and State-of-Charge (SoC) determination in electrochemical batteries and cells using designed perturbation signals." Thesis, University of Sheffield, 2015. http://etheses.whiterose.ac.uk/9156/.

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Samolyk, Mateusz, and Jakub Sobczak. "Development of an algorithm for estimating Lead-Acid Battery State of Charge and State of Health." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2937.

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In this paper, a state of charge (SOC) and a state of health (SOH) estimation method for lead-acid batteries are presented. In the algorithm the measurements of battery’s terminal voltage, current and temperature are used in the process of SOC calculation. The thesis was written in cooperation with Micropower AB. The algorithm was designed to fulfill the specific requirements of the electric vehicles application: an error below 5% of SOC, computational simplicity and the possibility of being implemented in a basic programming languages. The current used method at Micropower, Coulomb counting,

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Kerley, Ross Andrew. "Automotive Lead-Acid Battery State-of-Health Monitoring System." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/64870.

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This thesis describes the development of a system to continuously monitor the battery in a car and warn the user of an upcoming battery failure. An automotive battery endures enormous strain when it starts the engine, and when it supplies loads without the engine running. Note that the current during a cranking event often exceeds 500 Amperes. Despite the strains, a car battery still typically lasts 4-6 years before requiring replacement. There is often no warning of when a battery should be replaced and there is never a good time for a battery failure. All currently available lead-acid batt

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Hyun, Ji Hoon. "State of Health Estimation System for Lead-Acid Car Batteries Through Cranking Voltage Monitoring." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/71796.

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The work in this thesis is focused on the development and validation of an automotive battery monitoring system that estimates the health of a lead-acid battery during engine cranking and provides a low state of health (SOH) warning of potential battery failure. A reliable SOH estimation should assist users in preventing a sudden battery failure and planning for battery replacement in a timely manner. Most commercial battery health estimation systems use the impedance of a battery to estimate the SOH with battery voltage and current; however, using a current sensor increases the installation

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Urbain, Matthieu. "Modélisation électrique et énergétique des accumulateurs Li-Ion. Estimation en ligne de la SOC et de la SOH." Thesis, Vandoeuvre-les-Nancy, INPL, 2009. http://www.theses.fr/2009INPL028N/document.

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Ce mémoire traite de la modélisation électrique des accumulateurs lithium-ion, de l’estimation de leur état de charge (SOC) et de leur état de santé (SOH). Le premier chapitre revient sur les généralités concernant la technologie lithium-ion : caractéristiques, performances, constitution de l’élément de stockage, choix et nature des électrodes, conséquences qui en découlent d’un point de vue énergétique. Le principe de fonctionnement et les équations générales des phénomènes électrochimiques sont aussi développés. Des exemples d’application dans différents secteurs industriels sont ensuite pro

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Lièvre, Aurélien. "Développement d'un système de gestion de batterie lithium-ion à destination de véhicules "mild hybrid" : détermination des indicateurs d'état (SoC, SoH et SoF)." Thesis, Lyon 1, 2015. http://www.theses.fr/2015LYO10065/document.

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Les véhicules hybrides se démocratisent avec une utilisation croissante des éléments de stockage à base de lithium-ion. Dans ce contexte d'exploitation, le type d'usage est atypique et dépend fortement des stratégies de répartition des énergies au sein du véhicule. Parmi les hybridations, la catégorie "mild hybrid" conserve la motorisation thermique pour l'autonomie qu'elle apporte, et lui adjoint une machine électrique associée à un élément de stockage réversible, afin de permettre une récupération de l'énergie cinétique du véhicule. L'objet de ces travaux porte sur la mise en place d'algorit

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Urbain, Matthieu. "Modélisation électrique et énergétique des accumulateurs Li-Ion. Estimation en ligne de la SOC et de la SOH." Electronic Thesis or Diss., Vandoeuvre-les-Nancy, INPL, 2009. http://www.theses.fr/2009INPL028N.

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Ce mémoire traite de la modélisation électrique des accumulateurs lithium-ion, de l’estimation de leur état de charge (SOC) et de leur état de santé (SOH). Le premier chapitre revient sur les généralités concernant la technologie lithium-ion : caractéristiques, performances, constitution de l’élément de stockage, choix et nature des électrodes, conséquences qui en découlent d’un point de vue énergétique. Le principe de fonctionnement et les équations générales des phénomènes électrochimiques sont aussi développés. Des exemples d’application dans différents secteurs industriels sont ensuite pro

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Nazer, Rouba Al. "Système de mesure d'impédance électrique embarqué, application aux batteries Li-ion." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENT007/document.

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La mesure d'impédance électrique en embarqué sur véhicule est un sujet clé pour améliorer les fonctions de diagnostic d'un pack batterie. On cherche en particulier à fournir ainsi des mesures supplémentaires à celles du courant pack et des tensions cellules, afin d'enrichir les indicateurs de vieillissement dans un premier temps, et d'état de santé et de charge dans un second temps. Une méthode classique de laboratoire pour obtenir des mesures d'impédance d'une batterie est la spectroscopie d'impédance électrochimique (ou EIS). Elle consiste à envoyer un signal sinusoïdal en courant (ou tensio

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Abdennadher, Mohamed Karim. "Étude et élaboration d’un système de surveillance et de maintenance prédictive pour les condensateurs et les batteries utilisés dans les Alimentations Sans Interruptions (ASI)." Thesis, Lyon 1, 2010. http://www.theses.fr/2010LYO10101/document.

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Pour assurer une énergie électrique de qualité et de façon permanente, il existe des systèmes électroniques d’alimentation spécifiques. Il s’agit des Alimentations Sans Interruptions (ASI). Une ASI comme tout autre système peut tomber en panne ce qui peut entrainer une perte de redondance. Cette perte induit une maintenance corrective donc une forme d’indisponibilité ce qui représente un coût. Nous proposons dans cette thèse de travailler sur deux composants parmi les plus sensibles dans les ASI à savoir les condensateurs électrolytiques et les batteries au plomb. Dans une première phase, nous

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EZEMOBI, ETHELBERT NWABUGWU. "Battery States Monitoring and its Application in Energy Optimization of Hybrid Electric Vehicles." Doctoral thesis, Politecnico di Torino, 2022. https://hdl.handle.net/11583/2970996.

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Books on the topic "State of Charge (SoC) Monitoring"

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Intelligent Lithium-Ion Battery State of Charge (SOC) Estimation Methods. Cambridge Scholars Publishing, 2024.

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Book chapters on the topic "State of Charge (SoC) Monitoring"

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Deng, Dan, Daniel-Ioan Stroe, Jialu Qiao, et al. "Battery State of Charge Estimation." In Multidimensional Lithium-Ion Battery Status Monitoring. CRC Press, 2022. http://dx.doi.org/10.1201/9781003333791-3.

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Kang, Hang-Bong. "Monitoring Driver’s State and Predicting Unsafe Driving Behavior." In Algorithm & SoC Design for Automotive Vision Systems. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9075-8_6.

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Sanín, Rafael, Mauricio Fernández-Montoya, Maria Alejandra Garzón-Vargas, and Alejandro Velásquez-López. "Battery State of Charge Estimation Error Comparison Across Different OCV-SOC Curve Approximating Methods." In Communications in Computer and Information Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31019-6_51.

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Chowdhary, Rameez Raja, Manju K. Chattopadhyay, and Raj Kamal. "IoT-Based State of Charge and Temperature Monitoring System for Mobile Robots." In Lecture Notes in Networks and Systems. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3172-9_39.

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Yue, Changxi, Yufeng Sun, Jicheng Yu, Siyuan Liang, Boyang Ma, and Shengzhong Liu. "A High-Precision Measurement Method for Lithium-Ion Batteries Based on Aging Trajectory Transfer and Hardware-in-the-Loop Simulation." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-4856-6_13.

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Abstract Accurate measurement of the state of charge (SOC) in lithium-ion batteries is crucial for battery management systems in electric vehicles and fair transactions at battery swapping stations. However, battery aging leads to nonlinear variations in capacity and internal resistance, posing challenges for precise SOC estimation. To address this issue, this paper proposes a high-precision measurement method based on aging trajectory transfer and hardware-in-the-loop (HIL) simulation. Firstly, a two-stage aging trajectory transfer prediction model is established, utilizing aging data from st

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Zhang, Dongjie, Lin Hu, Qingtao Tian, and Changfu Zou. "A Research of Different Energy Management Strategies of Lithium-ion Battery-Ultracapacitor Hybrid Energy Storage System." In Lecture Notes in Mechanical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1876-4_87.

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AbstractGiven the exacerbating effect of fossil fuel use in conventional vehicles on the greenhouse effect, the imperative development of electric vehicle technology becomes evident. To address the high energy and power density demands of electric vehicles, a lithium-ion battery-ultracapacitor hybrid energy storage system proves effective. This study, utilizing ADVISOR and Matlab/Simulink, employs an electric vehicle prototype for modeling and simulating both logic threshold and fuzzy logic control strategies. It aims to analyze the average output power and state of charge (SOC) of the lithium

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Jamila, El Haini, and Nouira Taoufik. "A Review of the Estimation of State of Charge (SOC) and State of Health (SOH) of Li-Ion Batteries in Electric Vehicles." In Technical and Technological Solutions Towards a Sustainable Society and Circular Economy. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56292-1_42.

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Nair, Pratheesh Sivaraman, Tomislav Bukic, Dominik Burnner, Georgios Koutroulis, and Milan Zivadinovic. "AI-Based Power Split Strategy for Hybrid Commercial Vehicle Applications." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70392-8_137.

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AbstractIn the rapidly evolving landscape of hybrid commercial vehicle technology, integrating artificial intelligence (AI) with fuel cell applications offers a promising frontier for efficient, sustainable and eco-friendly road freight system. There has been many different approaches on optimization of power split between the electric motor and the fuel cell system (FCS). Conventional approaches use quadratic optimization to determine the optimal power from the electric motor at each discrete grid point along the route, with initial and final battery state of charge (SoC) as constraints. This

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Nazemian, Amin, Evangelos Boulougouris, and Myo Zin Aung. "Simulation of Hybrid Fuel Cell-Battery Propulsion System Scrutinizing Multi-scheme Energy Management for a CTV Boat." In Lecture Notes in Mobility. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-89444-2_62.

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Abstract This paper proposes a model of a hybrid fuel cell-battery propulsion system for a Crew Transfer Vessel (CTV). A multi-scheme energy management strategy is also applied to the EMS block to optimize energy flow. A fuel cell-battery hybrid system was developed by integrating PEM fuel cells with Li-ion batteries to provide electricity to the propeller propulsion system, and hotel load. Accordingly, a hybrid battery/fuel cell propulsion system with the capability of both charging the battery at both stations and bunkering the fuel tanks will be proposed. During cruising, docking, stopping,

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Hossain, Md Ismail, Khandoker Mainul Islam, Tarifuzzaman Riyad, Md Rafsan Jany, Al Shahriar Zishan, and Mohammad Nasir Uddin. "Gaussian Process Regression for State of Charge Prediction: Overcoming Temperature Variability in Li-ion Battery Applications." In Computational Intelligence and Machine Learning. Soft Computing Research Society, 2024. https://doi.org/10.56155/978-81-975670-5-6-10.

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Accurately predicting the State of Charge (SOC) in lithium-ion batteries is essential for efficient energy management in electric vehicles. Due to the nonlinear characteristics of battery behavior, which depend heavily on temperature and operating conditions, SOC estimation presents a significant engineering challenge. This study proposes a data-driven approach using Gaussian Process Regression (GPR) to predict SOC, leveraging a comprehensive dataset with voltage, current, temperature, and average historical measurements. The model was trained and optimized through Bayesian hyperparameter tuni

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Conference papers on the topic "State of Charge (SoC) Monitoring"

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Makuwatsine, Tatenda Trevor, and Manjeet Singh. "State of Charge (SOC) and State of Health (SOH) Estimation for Electric Vehicle Battery." In 2024 International Conference on Computer, Electronics, Electrical Engineering & their Applications (IC2E3). IEEE, 2024. https://doi.org/10.1109/ic2e362166.2024.10827735.

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Song, Ningfei, Nanlin Jin, Jingchen Wang, et al. "State of Charge Estimation for Lithium-Ion Batteries Based on Informer-LSTM Hybrid Network." In 2024 21st International SoC Design Conference (ISOCC). IEEE, 2024. http://dx.doi.org/10.1109/isocc62682.2024.10762752.

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Mala, R. C., and Samith Suvarna. "Long-Short-term Memory Neural Network to Predict State of Charge (SOC)." In 2024 Asia Pacific Conference on Innovation in Technology (APCIT). IEEE, 2024. http://dx.doi.org/10.1109/apcit62007.2024.10673547.

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Yadav, Anshul Kumar, Rajesh Kumar, Anil Kumar Saini, et al. "Edge Computing Enabled Battery State of Charge(SoC) Estimation Using TinyML Techniques." In 2024 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES). IEEE, 2024. https://doi.org/10.1109/pedes61459.2024.10961505.

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Wang, Hanrui, Dejie Zhang, Mei Yan, et al. "Estimation of State of Charge (SOC) for Lithium Iron Phosphate Batteries Based on SHEKF Algorithm." In 2024 8th CAA International Conference on Vehicular Control and Intelligence (CVCI). IEEE, 2024. https://doi.org/10.1109/cvci63518.2024.10830057.

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Feng, Yong, Fengling Han, Rebecca Yang, Yanmin Wang, Fan Bai, and Nguyen-Vu Truong. "Sliding Mode Control Strategy for State-of-Charge (SoC) Balancing in Lithium-ion Battery Packs*." In 2024 13th International Conference on Control, Automation and Information Sciences (ICCAIS). IEEE, 2024. https://doi.org/10.1109/iccais63750.2024.10814266.

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Sasikumar, M., V. Indumathi, R. Gopalakrishnan, P. S. Sudhakar, S. Sridharnish, and V. Sitheshwaran. "Implementation of Deep Learning Algorithm to Estimate the State of Charge (SOC) of Lithium Ion Battery." In 2025 3rd International Conference on Device Intelligence, Computing and Communication Technologies (DICCT). IEEE, 2025. https://doi.org/10.1109/dicct64131.2025.10986646.

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Pham, Huan L., J. Eric Dietz, Douglas E. Adams, and Nathan D. Sharp. "Lithium-Ion Battery Cell Health Monitoring Using Vibration Diagnostic Test." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-63962.

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With their superior advantages of high capacity and low percentage of self-discharge, lithium-ion batteries have become the most popular choice for power storage in electric vehicles. Due to the increased potential for long life of lithium-ion batteries in vehicle applications, manufacturers are pursuing methodologies to increase the reliability of their batteries. This research project is focused on utilizing non-destructive vibration diagnostic testing methods to monitor changes in the physical properties of the lithium-ion battery electrodes, which dictate the states of charge (SOC) and sta

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Hao, Huang, and Kangpei Meng. "State estimation method of square power battery based on ultrasonic guided wave." In 6th International Conference on Structural Health Monitoring and Integrity Management, 8 - 10 November 2024, Zhengzhou. NDT.net, 2025. https://doi.org/10.58286/31023.

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In order to establish a more accurate and stable battery charge state prediction model, a new ultrasonic guided wave signature, signal envelope, is proposed in this paper to predict battery SOC with machine learning. Firstly, ultrasonic characteristic parameters of experimental data are extracted by various algorithms, then the battery state is predicted by several machine learning methods, and finally, these results are analyzed to obtain the most accurate and stable SOC prediction machine learning model. The results show that the ultrasonic envelope signal is closely related to the state of

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Luciani, Sara, Stefano Feraco, Angelo Bonfitto, Andrea Tonoli, Nicola Amati, and Maurizio Quaggiotto. "A Machine Learning Method for State of Charge Estimation in Lead-Acid Batteries for Heavy-Duty Vehicles." In ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/detc2021-68469.

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Abstract In the automotive framework, an accurate assessment of the State of Charge (SOC) in lead-acid batteries of heavy-duty vehicles is of major importance. SOC is a crucial battery state that is non-observable. Furthermore, an accurate estimation of the battery SOC can prevent system failures and battery damage due to a wrong usage of the battery itself. In this context, a technique based on machine learning for SOC estimation is presented in this study. Thus, this method could be used for safety and performance monitoring purposes in electric subsystem of heavy-duty vehicles. The proposed

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Reports on the topic "State of Charge (SoC) Monitoring"

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Yang, Yu, Hen-Geul Yeh, and Cesar Ortiz. Battery Management System Development for Electric Vehicles and Fast Charging Infrastructure Improvement. Mineta Transportation Institute, 2024. http://dx.doi.org/10.31979/mti.2024.2325.

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The electric vehicle (EV) has become increasingly popular due to its being zero-emission. However, a significant challenge faced by EV drivers is the range anxiety associated with battery usage. Addressing this concern, this project develops a more efficient battery management system (BMS) for electric vehicles based on a real-time, state-of-charge (SOC) estimation. The proposed study delivers three modules: (1) a new equivalent circuit model (ECM) for lithium-ion batteries, (2) a new SOC estimator based on the moving horizon method, and (3) an on-board FPGA implementation of the classical Cou

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Saldivar-Carranza, Enrique D., Tom Platte, Terri Wills, James Sturdevant, and Darcy M. Bullock. Business Processes to Prioritize Traffic Signal Retiming and Assess the Impact of Retiming Activities. Purdue University, 2025. https://doi.org/10.5703/1288284317807.

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The Indiana Department of Transportation (INDOT) manages over 2,000 traffic signals in the State. It is unfeasible to identify systemwide improvement opportunities by evaluating the performance of thousands of traffic signals on monitoring dashboards. This report describes how a scalable technique based on connected vehicle (CV) trajectory data systematically evaluates performance at the movement level to prioritize retiming and maintenance activities. In total, eleven timing changes were implemented at nine traffic signals over various time-of-day (TOD) periods using the proposed approach. Th

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Cooper, Christopher, Jacob McDonald, and Eric Starkey. Wadeable stream habitat monitoring at Congaree National Park: 2018 baseline report. National Park Service, 2021. http://dx.doi.org/10.36967/nrr-2286621.

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The Southeast Coast Network (SECN) Wadeable Stream Habitat Monitoring Protocol collects data to give park resource managers insight into the status of and trends in stream and near-channel habitat conditions (McDonald et al. 2018a). Wadeable stream monitoring is currently implemented at the five SECN inland parks with wadeable streams. These parks include Horseshoe Bend National Military Park (HOBE), Kennesaw Mountain National Battlefield Park (KEMO), Ocmulgee Mounds National Historical Park (OCMU), Chattahoochee River National Recreation Area (CHAT), and Congaree National Park (CONG). Streams

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Nilsson Lewis, Astrid, Kaidi Kaaret, Eileen Torres Morales, Evelin Piirsalu, and Katarina Axelsson. Accelerating green public procurement for decarbonization of the construction and road transport sectors in the EU. Stockholm Environment Institute, 2023. http://dx.doi.org/10.51414/sei2023.007.

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Public procurement of goods and services contributes to about 15% of global greenhouse gas emissions. In the EU, public purchasing represents 15% of its GDP, acting as a major influencer on the market through the products and services acquired by governments from the local to national levels. The public sector has a role to play in leveraging this purchasing power to achieve the best societal value for money, particularly as we scramble to bend the curve of our planet’s warming. Globally, the construction and transport sectors each represent about 12% of government procurements’ GHG emissions.

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Weissinger, Rebecca. Trends in water quality at Bryce Canyon National Park, water years 2006–2021. Edited by Alice Wondrak Biel. National Park Service, 2022. http://dx.doi.org/10.36967/2294946.

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The National Park Service collects water-quality samples on a rotating basis at three fixed water-quality stations in Bryce Canyon National Park (NP): Sheep Creek, Yellow Creek, and Mossy Cave Spring. Data collection began at Sheep Creek and Yellow Creek in November 2005 and at Mossy Cave in July 2008. Data on in-situ parameters, fecal-coliform samples, major ions, and nutrients are collected monthly, while trace elements are sampled quarterly. This report analyzes data from the beginning of the period of record for each station through water year 2021 to test for trends over time. Concentrati

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Raikow, David, Mark Wasser, Amanda McCutcheon, and Anne Farahi. Trends in water quality of Waikolu Stream, Kalaupapa National Historical Park, Moloka?i, Hawaii, 2007?2017. National Park Service, 2024. http://dx.doi.org/10.36967/2302153.

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Water quality was monitored in Waikolu Stream, Kalaupapa National Historical Park, Moloka?i, Hawa?i from 2007-2017. Water was collected for nutrient analyses and a sonde equipped with multiple probes was used to measure water quality parameters. The sampling regime was based on a split-panel of permanently established or ?fixed? sites sampled during each sampling effort, and ?temporary? sites of randomly assigned locations, for each sampling effort. Results included: ? NO-3 + NO-2 regularly exceeded state water quality criteria. ? TP exceeded state water quality criteria once out of three quar

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Brosh, Arieh, David Robertshaw, Yoav Aharoni, Zvi Holzer, Mario Gutman, and Amichai Arieli. Estimation of Energy Expenditure of Free Living and Growing Domesticated Ruminants by Heart Rate Measurement. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7580685.bard.

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Research objectives were: 1) To study the effect of diet energy density, level of exercise, thermal conditions and reproductive state on cardiovascular function as it relates to oxygen (O2) mobilization. 2) To validate the use of heart rate (HR) to predict energy expenditure (EE) of ruminants, by measuring and calculating the energy balance components at different productive and reproductive states. 3) To validate the use of HR to identify changes in the metabolizable energy (ME) and ME intake (MEI) of grazing ruminants. Background: The development of an effective method for the measurement of

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Totten, Annette, Dana M. Womack, Marian S. McDonagh, et al. Improving Rural Health Through Telehealth-Guided Provider-to-Provider Communication. Agency for Healthcare Research and Quality, 2022. http://dx.doi.org/10.23970/ahrqepccer254.

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Objectives. To assess the use, effectiveness, and implementation of telehealth-supported provider-to-provider communication and collaboration for the provision of healthcare services to rural populations and to inform a scientific workshop convened by the National Institutes of Health Office of Disease Prevention on October 12–14, 2021. Data sources. We conducted a comprehensive literature search of Ovid MEDLINE®, CINAHL®, Embase®, and Cochrane CENTRAL. We searched for articles published from January 1, 2015, to October 12, 2021, to identify data on use of rural provider-to-provider telehealth

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Banin, Amos, Joseph Stucki, and Joel Kostka. Redox Processes in Soils Irrigated with Reclaimed Sewage Effluents: Field Cycles and Basic Mechanism. United States Department of Agriculture, 2004. http://dx.doi.org/10.32747/2004.7695870.bard.

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The overall objectives of the project were: (a) To measure and study in situ the effect of irrigation with reclaimed sewage effluents on redox processes and related chemical dynamics in soil profiles of agricultural fields. (b) To study under controlled conditions the kinetics and equilibrium states of selected processes that affect redox conditions in field soils or that are effected by them. Specifically, these include the effects on heavy metals sorption and desorption, and the effect on pesticide degradation. On the basis of the initial results from the field study, increased effort was de

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Galili, Naftali, Roger P. Rohrbach, Itzhak Shmulevich, Yoram Fuchs, and Giora Zauberman. Non-Destructive Quality Sensing of High-Value Agricultural Commodities Through Response Analysis. United States Department of Agriculture, 1994. http://dx.doi.org/10.32747/1994.7570549.bard.

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The objectives of this project were to develop nondestructive methods for detection of internal properties and firmness of fruits and vegetables. One method was based on a soft piezoelectric film transducer developed in the Technion, for analysis of fruit response to low-energy excitation. The second method was a dot-matrix piezoelectric transducer of North Carolina State University, developed for contact-pressure analysis of fruit during impact. Two research teams, one in Israel and the other in North Carolina, coordinated their research effort according to the specific objectives of the proj

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