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Journal articles on the topic 'Embedded battery'

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Author: Grafiati

Published: 14 March 2023

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1

Niu, Jianna, George You Zhou, and Tong Wu. "Embedded Battery Energy Storage System for Diesel Engine Test Applications." International Journal of Materials, Mechanics and Manufacturing 3, no. 4 (2015): 294–98. http://dx.doi.org/10.7763/ijmmm.2015.v3.213.

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2

Kulkarni, V. A., and G. R. Udupi. "Software Power Measurement of ARM Processor Based Embedded System." European Journal of Engineering and Technology Research 1, no. 5 (July 27, 2018): 5–9. http://dx.doi.org/10.24018/ejeng.2016.1.5.184.

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Energy consumption is very crucial for battery powered Embedded Systems. In recent times, embedded system functionalities are increasing by many folds. But the battery technology is not advancing in the same pace. This necessitates the need to reduce energy consumption of battery powered embedded applications. The total energy of a typical embedded system is due to energy of software and hardware components. Once we know the total energy, we can estimate battery life accurately. Conversely, various measures can be taken to increase battery life. This paper presents measurement based approach to find energy cost associated with ARM instructions.

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3

Rakhmatov, Daler, and Sarma Vrudhula. "Energy management for battery-powered embedded systems." ACM Transactions on Embedded Computing Systems 2, no. 3 (August 2003): 277–324. http://dx.doi.org/10.1145/860176.860179.

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4

Madsen, Anne K., and Darshika G. Perera. "Composing Optimized Embedded Software Architectures for Physics-Based EKF-MPC Smart Sensor for Li-Ion Battery Cell Management." Sensors 22, no. 17 (August 26, 2022): 6438. http://dx.doi.org/10.3390/s22176438.

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Efficient battery technology is imperative for the adoption of clean energy automotive solutions. In addition, efficient battery technology extends the useful life of the battery as well as provides improved performance to fossil fuel technology. Model predictive control (MPC) is an effective way to operate battery management systems (BMS) at their maximum capability, while maintaining the safety requirements. Using the physics-based model (PBM) of the battery allows the control system to operate on the chemical and physical process of the battery. Since these processes are internal to the battery and are physically unobservable, the extended Kalman filter (EKF) serves as a virtual observer that can monitor the physical and chemical properties that are otherwise unobservable. These three methods (i.e., PBM, EKF, and MPC) together can prolong the useful life of the battery, especially for Li-ion batteries. This capability is not limited to the automotive industry: any real-world smart application can benefit from a portable/mobile efficient BMS, compelling these systems to be executed on resource-constrained embedded devices. Furthermore, the intrinsic adaptive control process of the PBM is uniquely suited for smart systems and smart technology. However, the sheer computational complexity of PBM for MPC and EKF prevents it from being realized on highly constrained embedded devices. In this research work, we introduce a novel, unique, and efficient embedded software architecture for a PB-EKF-MPC smart sensor for BMS, specifically on embedded devices, by addressing the computational complexity of PBM. Our proposed embedded software architecture is created in such a way to be executed on a 32-bit embedded microprocessor running at 100 MHz with a limited memory of 128 KB, and still obtains an average execution time of 4.8 ms.

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5

Lee, Noah, Chen Hon Nee, Seong Shan Yap, Kwong Keong Tham, Ah Heng You, Seong Ling Yap, and Abdul Kariem Bin Mohd Arof. "Capacity Sizing of Embedded Control Battery–Supercapacitor Hybrid Energy Storage System." Energies 15, no. 10 (May 20, 2022): 3783. http://dx.doi.org/10.3390/en15103783.

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A battery–supercapacitor hybrid energy storage system is investigated as a solution to reduce the high-power delivery stress on the battery. An optimally-sized system can further enhance the storage and cost efficiency. This paper discusses several possible problems in the sizing of a battery–supercapacitor hybrid energy storage system for practical applications. A sizing method that utilises data collected from a fully active embedded control hybrid energy system is proposed. The feasibility of the method is then tested on three load profiles that represent the load demand of inter- and intra-applications with a battery–supercapacitor hybrid energy storage system. The result is compared to a battery-only single energy storage system. The results verified that the number of batteries required in the hybrid energy storage system is reduced by at least 50% compared to the battery-only single energy storage system.

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6

Yoo, Sunggoo, Chonggi Hong, Kil To Chong, and Namo Seul. "Analysis of Pouch Performance to Ensure Impact Safety of Lithium-Ion Battery." Energies 12, no. 15 (July 25, 2019): 2865. http://dx.doi.org/10.3390/en12152865.

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The use of mobile devices equipped with embedded batteries is increasing. These embedded batteries are generally lithium-ion batteries in the form of a pouch. However, if an impact is applied to the embedded battery, it can potentially lead to fire and explosion. In this study, we analyzed the safety of the battery, depending on the material and shape of the surrounding pouch. Through tensile strength assessment, an elongation measurement experiment, and impact evaluation, the elements that can improve safety were found. The analysis results confirmed that, as the tensile strength and elongation increased, the impact defect rate decreased. Applying these findings to battery manufacturing can help secure impact safety.

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7

Simatupang, Desmon, Abdulraouf Benshatti, and Sung-Yeul Park. "Battery Internal Temperature Measurement Using LC Resonant Tank for Battery Management Systems." Batteries 9, no. 2 (February 2, 2023): 104. http://dx.doi.org/10.3390/batteries9020104.

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This paper suggests an embedded battery impedance measurement based on an Inductor Capacitor (LC) resonant tank to measure the battery’s internal temperature for battery management systems (BMS). The purpose of the BMS is to provide state-of-charge (SoC) balancing and the preheating mechanism at sub-zero temperatures. Battery Impedance Spectroscopy (BIS) for battery internal temperature measurement is achieved by an LC resonant tank connected to the batteries in parallel to induce created resonant current and voltage into the battery. The peaks of the voltage and current waveforms are measured and recorded. Then, the resistance of the battery can be calculated by comparing the peak voltage and current waveforms. Since the resistance of the battery is affected by the battery’s internal temperature, the internal temperature of the battery can be estimated. The benefit of using the LC tank for the battery’s internal temperature is to reduce data processing since no window and Fast Fourier Transform (FFT) is needed for this method. In addition, the proposed method measures the battery’s internal temperature without any internal or external temperature sensor. Power Simulation (PSIM) simulation software is used in this proposed method. Panasonic batteries 18650 and a dSPACE DS1104 are used for the experiment to verify the proposed method. The proposed method shows that the LC resonant tank can measure three batteries B1, B2, and B3 internal resistance with 17.87%, 18.14%, and 17.73% errors compared to the Frequency Response Analyzer (FRA). In addition, the total time needed for balancing is 400 s, and the total energy consumed by the preheating mechanism is 0.214%/°C to preheat the lithium-ion batteries (LIBs) from −5 °C to 10 °C.

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8

Assaouy, Mohammed, Ouadoudi Zytoune, and Mohamed Ouadou. "Battery Recovery-Aware Optimization for Embedded System Communications." Wireless Personal Communications 110, no. 4 (October 11, 2019): 1929–46. http://dx.doi.org/10.1007/s11277-019-06820-1.

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9

Simunic, T., L. Benini, and G. De Micheli. "Energy-efficient design of battery-powered embedded systems." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 9, no. 1 (February 2001): 15–28. http://dx.doi.org/10.1109/92.920814.

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10

Fedorova, Anna A. "Empirical and physics-based approaches to estimate states of lithium-ion battery." Zhurnal Srednevolzhskogo Matematicheskogo Obshchestva 21, no. 2 (June 30, 2019): 259–68. http://dx.doi.org/10.15507/2079-6900.21.201902.259-268.

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Lithium-ion batteries are integral parts of our life due to the rapid increase of applications which require batteries for their exploitation. Thus, there is a market demand to produce lithium-ion batteries for a huge number of applications from electric vehicles to energy storages. Battery Management System (BMS) is developed to maintain safe battery exploitation conditions. Most BMSs are embedded systems that have physical memory limits. Therefore, battery model should be easy to simulate to be integrated into BMS for states estimation. In the present paper we intend to compare empirical and physics-based approaches to estimate lithium-ion battery states with respect to their possibility of implementation in the embedded system. We will use Kalman filter to estimate battery states by means of the mentioned models.

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11

Lee, Chi-Yuan, Chia-Hung Chen, John-Shong Cheong, Yun-Hsiu Chien, and Yi-Chuan Lin. "Flexible 5-in-1 Microsensor Embedded in the Proton Battery for Real-Time Microscopic Diagnosis." Membranes 11, no. 4 (April 8, 2021): 276. http://dx.doi.org/10.3390/membranes11040276.

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The proton battery possesses water electrolysis, proton storage and discharging functions simultaneously, and it can be manufactured without expensive metals. Use the principle of proton exchange membrane water electrolysis for charging, store it in the activated carbon on the hydrogen side and use the principle of proton exchange membrane fuel cell for discharge when needed. According to the latest literature, it is difficult to obtain the exact important physical parameters inside the proton battery (e.g., voltage, current, temperature, humidity and flow), and the important physical parameters are correlated with each other, which have critical influence on the performance, lifetime and health status of the proton battery. At present, the condition of the proton battery is judged indirectly only by external measurement, the actual situation inside the proton battery cannot be obtained accurately and instantly. Therefore, this study uses micro-electro-mechanical systems (MEMS) technology to develop a flexible 5-in-1 microsensor, which is embedded in the proton battery to obtain five important physical parameters instantly, so that the condition inside the proton battery can be mastered more precisely, so as to prolong the battery life and enhance the proton battery performance.

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12

Locorotondo, Edoardo, Fabio Corti, Luca Pugi, Lorenzo Berzi, Alberto Reatti, and Giovanni Lutzemberger. "Design of a Wireless Charging System for Online Battery Spectroscopy." Energies 14, no. 1 (January 4, 2021): 218. http://dx.doi.org/10.3390/en14010218.

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This paper presents the design procedure of an electric circuit that can perform the battery state diagnosis and, simultaneously, provide its charging. A fast and embedded impedance measurement method is also proposed; this is based on a broadband current signal excitation on the battery during the constant current charging phase. The proposed solution performs the electrochemical impedance spectroscopy (EIS), which is known to provide useful information about battery chemical–physical property changes due to aging or failure events. To demonstrate the functionalities of the proposed method, the spectroscopy is implemented in the control in the wireless charging system. An EIS charging test is simulated on an equivalent circuit model, which emulates the battery impedance properties in a specified frequency band. Circuit parameters are evaluated by experimental data. According to the obtained results, the proposed method allows us to reach an accurate estimation of the battery state and represents a promising solution for an embedded diagnostic of battery health thanks to its simplicity and speed.

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13

Shang, Yu Xiang, Zhen Kun Lei, and Rui Mao. "Preparation and Testing of Carbon Fiber Reinforced Composites Embedded with Lithium-Ion Polymer Batteries." Materials Science Forum 1058 (April 5, 2022): 199–203. http://dx.doi.org/10.4028/p-1uw59e.

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Vehicle lightweight promises to drive down the maintenance quality and increase energy efficiency in transportation with the safe and strength performance. The use of fiber reinforced polymer composite materials structural battery vehicles is recognized as an essential enabling technology for achieving high bearing capacity and energy storage capacity. At the same time it improves the energy storage capacity, the overall structural energy storage and space utilization of new energy vehicles. In this study we bring an idea to fabricate composites with integrated lithium-ion pouch batteries. The whole preparation process was carried out at room temperature to prevent thermal damage on battery. Experimental results indicate that the cyclic working voltage and capacity of CFRP structure battery are basically consistent with the monomer lithium-ion polymer battery which obtained from Xinwei battery testing equipment. Therefore, the fabrication process does not damage the lithium-ion polymer battery.

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14

Lee, Chi-Yuan, Chia-Hung Chen, Chin-Yuan Yang, John-Shong Cheong, Yun-Hsiu Chien, and Yi-Chuan Lin. "Low-Temperature Flexible Micro Hydrogen Sensor Embedded in a Proton Battery for Real-Time Microscopic Diagnosis." Micromachines 12, no. 10 (October 5, 2021): 1215. http://dx.doi.org/10.3390/mi12101215.

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The proton battery is a very novel emerging research area with practicability. The proton battery has charging and discharging functions. It not only electrolyzes water: the electrolyzed protons can be stored but also released, which are combined with oxygen to generate electricity, and the hydrogen is not required; the hydrogen ions will be released from the battery. According to the latest document, the multiple important physical parameters (e.g., hydrogen, voltage, current, temperature, humidity, and flow) inside the proton battery are unlikely to be obtained accurately and the multiple important physical parameters mutually influence the data; they have critical effects on the performance, life, and health status of the proton battery. At present, the proton battery is measured only from the outside to indirectly diagnose the health status of battery; the actual situation inside the proton battery cannot be obtained instantly and accurately. This study uses micro-electro-mechanical systems (MEMS) technology to develop a low-temperature micro hydrogen sensor, which is used for monitoring the internal condition of the proton battery and judging whether or not there is hydrogen leakage, so as to enhance the safety.

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15

Lee, Yong-Duk, Sung-Yeul Park, and Soo-Bin Han. "Online Embedded Impedance Measurement Using High-Power Battery Charger." IEEE Transactions on Industry Applications 51, no. 1 (January 2015): 498–508. http://dx.doi.org/10.1109/tia.2014.2336979.

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16

Lahiri, K., A. Raghunathan, and S. Dey. "Efficient Power Profiling for Battery-Driven Embedded System Design." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 23, no. 6 (June 2004): 919–32. http://dx.doi.org/10.1109/tcad.2004.828137.

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17

Lee, Kyungsoo, Naehyuck Chang, Jianli Zhuo, Chaitali Chakrabarti, Sudheendra Kadri, and Sarma Vrudhula. "A fuel-cell-battery hybrid for portable embedded systems." ACM Transactions on Design Automation of Electronic Systems 13, no. 1 (January 2008): 1–34. http://dx.doi.org/10.1145/1297666.1297685.

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18

Jongerden, M., A. Mereacre, H. Bohnenkamp, B. Haverkort, and J. Katoen. "Computing Optimal Schedules of Battery Usage in Embedded Systems." IEEE Transactions on Industrial Informatics 6, no. 3 (August 2010): 276–86. http://dx.doi.org/10.1109/tii.2010.2051813.

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19

Lee, Chi-Yuan, Chia-Hung Chen, Chin-Yuan Yang, John-Shong Cheong, Yun-Hsiu Chien, and Yi-Chuan Lin. "Flexible 6-in-1 Microsensor for Real-Time Microscopic Monitoring of Proton Battery." Membranes 11, no. 8 (August 12, 2021): 615. http://dx.doi.org/10.3390/membranes11080615.

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According to the comparison between a proton battery and a proton exchange membrane fuel cell (PEMFC), the PEMFC requires oxygen and hydrogen for generating electricity, so a hydrogen tank is required, leading to larger volume of PEMFC. The proton battery can store hydrogen in the carbon layer, combined with the oxygen in the air to form water to generate electricity; thus, the battery cost and the space for a hydrogen tank can be reduced a lot, and it is used more extensively. As the proton battery is a new research area, multiple important physical quantities inside the proton battery should be further understood and monitored so as to enhance the performance of battery. The proton battery has the potential for practical applications, as well as water electrolysis, proton storage and discharge functions, and it can be produced without expensive metals. Therefore, in this study, we use micro-electro-mechanical systems (MEMS) technology to develop a diagnostic tool for the proton battery based on the developed microhydrogen sensor, integrated with the voltage, current, temperature, humidity and flow microsensors developed by this laboratory to complete a flexible integrated 6-in-1 microsensor, which is embedded in the proton battery to measure internal important physical parameters simultaneously so that the reaction condition in the proton battery can be mastered more accurately. In addition, the interaction of physical quantities of the proton battery are discussed so as to enhance the proton battery’s performance.

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20

Deng, Zhongwei, Lin Yang, Hao Deng, Yishan Cai, and Dongdong Li. "Polynomial approximation pseudo-two-dimensional battery model for online application in embedded battery management system." Energy 142 (January 2018): 838–50. http://dx.doi.org/10.1016/j.energy.2017.10.097.

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21

Lee, Chi-Yuan, Chia-Hung Chen, Yu-Chun Chen, and Xin-Fu Jiang. "A Flexible 7-in-1 Microsensor Embedded in a Hydrogen/Vanadium Redox Battery for Real-Time Microscopic Measurements." Membranes 13, no. 1 (December 30, 2022): 49. http://dx.doi.org/10.3390/membranes13010049.

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The latest document indicates that the hydrogen/vanadium redox flow battery has better energy density and efficiency than the vanadium redox flow battery, as well as being low-cost and light-weight. In addition, the hydrogen, electrical conductivity, voltage, current, temperature, electrolyte flow, and runner pressure inside the hydrogen/vanadium redox flow battery can influence its performance and life. Therefore, this plan will try to step into the hydrogen/vanadium redox flow battery stack and improve the vanadium redox flow battery of this R&D team, whereof the electrolyte is likely to leak during assembling, and the strong acid corrosion environment is likely to age or fail the vanadium redox flow battery and microsensors. Micro-electro-mechanical systems (MEMS) are used, which are integrated with the flexible 7-in-1 microsensor, which is embedded in the hydrogen/vanadium redox flow battery for internal real-time microscopic sensing and diagnosis.

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22

Tuang, Geng Ju, Nik Roslina Nik Hussin, and Zainal Azmi Zainal Abidin. "Unilateral rhinorrhoea and button battery: a case report." Family Medicine and Community Health 7, no. 3 (July 2019): e000137. http://dx.doi.org/10.1136/fmch-2019-000137.

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Unilateral rhinorrhoea in the paediatric age group could be an alarming sign that warrants a clinician attention. These patients are routinely brought to see general practitioner as parents may not be aware of the urgency to intervene surgically. Herein we describe a case of a toddler who presented initially to a general practitioner with unilateral nasal discharge. He was subsequently referred to the otorhinolaryngology department for unresolved rhinitis. The child was examined, and the diagnosis of an embedded foreign body was made. X-ray of the paranasal sinus unveiled an embedded button battery. An emergency endoscopic retrieval of the button battery was performed under general anaesthesia. Unfortunately, the case was complicated with a huge septal perforation.

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23

Miao, Xingyu, Jiayuan Wei, and Yongqi Ge. "Analysis and Design of the Battery Initial Energy Level with Task Scheduling for Energy-Harvesting Embedded Systems." Complexity 2021 (April 15, 2021): 1–16. http://dx.doi.org/10.1155/2021/5580631.

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When the energy-harvesting embedded system (EHES) is running, its available energy (harvesting energy and battery storage energy) seems to be sufficient overall. However, in the process of EHES task execution, an energy shortage may occur in the busy period such that system tasks cannot be scheduled. We call this issue the energy deception (ED) of the EHES. Aiming to address the ED issue, we design an appropriate initial energy level of the battery. In this paper, we propose three algorithms to judge the feasibility of the task set and calculate the appropriate initial energy level of the battery. The holistic energy evaluation (HEE) algorithm makes a preliminary judgment of the task set feasibility according to available energy and consumption energy. A worst-case response time-based initial energy level of the battery (WCRT-IELB) algorithm and an accurate cycle-initial energy level of the battery (AC-IELB) algorithm can calculate the proper initial battery capacity. We use the YARTISS tool to simulate the above three algorithms. We conducted 250 experiments on As Late As Possible (ALAP) and As Soon As Possible (ASAP) scheduling with the maximum battery capacities of 50, 100, 200, 300, and 400. The experimental results show that setting a reasonable initial energy level of the battery can effectively improve the feasibility of the task set. Among the 250 task sets, the HEE algorithm filtered 2.8% of them as infeasible task sets. When the battery capacity is set to 400, the WCRT-BIEL algorithm increases the success rates of the ALAP and ASAP by 17.2% and 26.8%, respectively. The AC-BIEL algorithm increases the success rates of the ALAP and ASAP by 18% and 26.8%, respectively.

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24

Huang, Chao. "FPGA-Based Battery Management System." Applied Mechanics and Materials 543-547 (March 2014): 792–95. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.792.

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This article introduces a battery management system of portable receiver or equipment based on a FPGA chip for control. This design can control the charge-discharge process and obtain the battery information through a SoPC, which can transfer the information to the upper computer for displaying and managing through the interface between the local and the network, or warn and deal with the abnormal condition according to the information. This design can be widely used in portable embedded system or digital system for power supply.

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25

Zhu, Hong Lei, Zheng Bin Wu, Da Long Wang, and Jia Yao Sun. "Design and Implementation of Distributed Battery Management System." Advanced Materials Research 608-609 (December 2012): 1039–42. http://dx.doi.org/10.4028/www.scientific.net/amr.608-609.1039.

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Based on the characteristics of power Li-ion battery, a distributed battery management system (BMS) is designed and implemented for electric vehicle (EV), which is composed of a master system and several measurement modules. The measurement modules are embedded into various numbers of cells and detect the status information of the battery. The system structure is highly flexible and reliable. The testing results of this BMS with a battery charge and discharge test equipment show that it can measure and display the status information of the battery precisely and reliably with a flexible structure, which supports EVs running safely and reliably.

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26

Bundalo, Zlatko V. "Energy efficient embedded systems and their application in wireless sensor networks." IOP Conference Series: Materials Science and Engineering 1208, no. 1 (November 1, 2021): 012002. http://dx.doi.org/10.1088/1757-899x/1208/1/012002.

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Abstract Embedded systems are specialised electronic systems that perform limited number of fixed operations and are used in many application areas. Such systems are based on using microprocessors for their implementation. Embedded systems are usually part of other systems where they are embedded into some embedding systems. They have to be efficient in electrical energy consumption, size of program code, time of operation, weight and cost. Embedded systems are inexpensive and are used in almost every electronic product or other electronic systems. Many embedded systems are mobile systems supplied by batteries and the available electrical energy must be used efficiently as much as possible. Application areas where embedded systems are used and where minimal consumption of energy is required are battery powered wireless sensor networks. The methods for reduction of energy consumption and for power management in embedded systems are considered and described in this paper. The accent is given on design and application of energy efficient embedded systems in wireless sensor networks and on possibilities to reduce energy consumption in such systems. The methods for energy harvesting, that are very attractive and very useful in wireless sensor networks applications, are also considered and described. One practically implemented battery supplied wireless sensor network for application for environmental data acquisition and monitoring in agriculture is described in the paper.

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27

Jeong, Tae-Hoon, and Ju-Yong Kim. "Development of Battery Protection Unit using Embedded Module and PCM." Journal of the Korean Institute of Illuminating and Electrical Installation Engineers 33, no. 10 (October 31, 2019): 43–51. http://dx.doi.org/10.5207/jieie.2019.33.10.043.

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28

Lee, Kyungsoo, Youngjin Cho, Jaehyun Park, Younghyun Kim, Jihun Kim, and Naehyuck Chang. "A Fuel-Cell-Battery Hybrid Platform for Portable Embedded Systems." IFAC Proceedings Volumes 41, no. 2 (2008): 2188–93. http://dx.doi.org/10.3182/20080706-5-kr-1001.00369.

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29

Suresh, Govindan, Andrew DeRouin, Ri Chen, and Keat Ghee Ong. "A Battery-Less Wireless Embedded Sensor for Wide Area Monitoring." Sensor Letters 14, no. 10 (October 1, 2016): 1054–60. http://dx.doi.org/10.1166/sl.2016.3651.

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30

Khan, I. A., F. Nasim, M. Choucair, S. Ullah, A. Badshah, and M. A. Nadeem. "Cobalt oxide nanoparticle embedded N-CNTs: lithium ion battery applications." RSC Advances 6, no. 2 (2016): 1129–35. http://dx.doi.org/10.1039/c5ra23222h.

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31

Song, Hee Jo, Jae-Chan Kim, Mingu Choi, Changhoon Choi, Mushtaq Ahmad Dar, Chan Woo Lee, Sangbaek Park, and Dong-Wan Kim. "Li2MnSiO4 nanorods-embedded carbon nanofibers for lithium-ion battery electrodes." Electrochimica Acta 180 (October 2015): 756–62. http://dx.doi.org/10.1016/j.electacta.2015.08.161.

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32

Meng, Fancheng, Xiaojing Fan, Aiming Xing, Han Liu, Changhao Lin, Zhuangzhuang Wang, Lingsong Xu, Lianxi Zheng, and Jiehua Liu. "Sodium polyacrylate-derived porous carbon nanosheets for high-performance lithium–sulfur batteries." Sustainable Energy & Fuels 3, no. 4 (2019): 942–47. http://dx.doi.org/10.1039/c8se00543e.

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33

Bai, Xuejun, Min Hou, Zhaoyu Yu, Chan Liu, Hui Cao, Dong Wang, and Junjie Fu. "An optimized 3D carbon matrix for high rate silicon anodes." RSC Advances 7, no. 53 (2017): 33521–25. http://dx.doi.org/10.1039/c7ra05647h.

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Luo, Shaochuan, Tianyi Wang, Hongyan Lu, Xiaoqian Xu, Gi Xue, Nan Xu, Yong Wang, and Dongshan Zhou. "Ultrasmall SnO2 nanocrystals embedded in porous carbon as potassium ion battery anodes with long-term cycling performance." New Journal of Chemistry 44, no. 27 (2020): 11678–83. http://dx.doi.org/10.1039/d0nj00323a.

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35

Xu, Yuanxian, Wenyue Li, Fan Zhang, Xiaolong Zhang, Wenjun Zhang, Chun-Sing Lee, and Yongbing Tang. "In situ incorporation of FeS nanoparticles/carbon nanosheets composite with an interconnected porous structure as a high-performance anode for lithium ion batteries." Journal of Materials Chemistry A 4, no. 10 (2016): 3697–703. http://dx.doi.org/10.1039/c5ta09138a.

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36

Wang, Zhuo, Zhuo Yu, Bingliang Wang, Zhaowei Guo, Nan Wang, Yonggang Wang, and Yongyao Xia. "Nano-Cu-embedded carbon for dendrite-free lithium metal anodes." Journal of Materials Chemistry A 7, no. 40 (2019): 22930–38. http://dx.doi.org/10.1039/c9ta09232c.

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Copper–organic framework-derived material is applied as a host for Li plating/stripping. The resulting anode exhibits dendrite-free Li deposition and high efficiency. The corresponding capacitor and battery display good electrochemical performance.

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37

Yang, Yang, Yufeng Jiang, Wenbin Fu, Xiao-Zhen Liao, Yu-Shi He, Wan Tang, Faisal M. Alamgir, and Zi-Feng Ma. "Cobalt phosphide embedded in a graphene nanosheet network as a high-performance anode for Li-ion batteries." Dalton Transactions 48, no. 22 (2019): 7778–85. http://dx.doi.org/10.1039/c9dt01240k.

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38

Lee, Chi-Yuan, Chin-Lung Hsieh, Chia-Hung Chen, Yen-Pu Huang, Chong-An Jiang, and Pei-Chi Wu. "A Flexible 5-In-1 Microsensor for Internal Microscopic Diagnosis of Vanadium Redox Flow Battery Charging Process." Sensors 19, no. 5 (February 28, 2019): 1030. http://dx.doi.org/10.3390/s19051030.

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Multiple important physical parameters in the vanadium redox flow battery are difficult to measure accurately, and the multiple important physical parameters (e.g., temperature, flow, voltage, current, pressure, and electrolyte concentration) are correlated with each other; all of them have a critical influence on the performance and life of vanadium redox flow battery. In terms of the feed of fuel to vanadium redox flow battery, the pump conveys electrolytes from the outside to inside for reaction. As the performance of vanadium redox flow battery can be tested only by an external machine—after which, the speed of pump is adjusted to control the flow velocity of electrolyte—the optimum performance cannot be obtained. There is a demand for internal real-time microscopic diagnosis of vanadium redox flow batteries, and this study uses micro-electro-mechanical systems (MEMS) technology to develop a flexible five-in-one (temperature, flow, voltage, current, and pressure) microsensor, which is embedded in vanadium redox flow battery, for real-time sensing. Its advantages include: (1) Small size and the simultaneous measurement of five important physical quantities; (2) elastic measurement position and accurate embedding; and (3) high accuracy, sensitivity, and quick response time. The flexible five-in-one microsensor embedded in the vanadium redox flow battery can instantly monitor the changes in different physical quantities in the vanadium redox flow battery during charging; as such, optimum operating parameters can be found out so that performance and life can be enhancec.

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Jain, Pranay, Sanjana Kumari, and Shreenivas B. "Framework for Real-Time Monitoring of Battery Performance in Electric Vehicles and Locating Charging Facilities Nearby." International Journal of Engineering and Advanced Technology 10, no. 6 (August 30, 2021): 38–43. http://dx.doi.org/10.35940/ijeat.f2980.0810621.

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Electric vehicles (EVs) are becoming more prevalent in the market. In a world where all vehicles are electric, it will be necessary to provide infrastructure on average highways that is similar to the energy consumption of the automobiles on that highway. As a result, a large transition from one type of energy carrier to electrical energy would be required. In comparison to where we are now, this translates into a significant increase in the carrying capacity of the power grid. Electric vehicles are in increasing demand because they have several advantages over gasoline-powered vehicles. On the other hand, limited battery power stations and a lack of infrastructure giving real-time vehicle performance parameters such as battery efficiency, durability, total distance travelled before being totally depleted, and so on should be considered. As a result, an embedded system is being developed in our project to address the aforementioned restrictions. The suggested research demonstrates all of the mathematical calculations of battery characteristics (including but not limited to battery efficiency and percentage durability), which aids in evaluating real-time batter performance. The system was tested and verified in laboratories using acceptable methodologies. In addition, a mobile application for the end-user is being created to provide information on battery parameters as well as the maximum distance it can travel till full discharge.

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Madani, Seyed Saeed, Raziye Soghrati, and Carlos Ziebert. "A Regression-Based Technique for Capacity Estimation of Lithium-Ion Batteries." Batteries 8, no. 4 (March 31, 2022): 31. http://dx.doi.org/10.3390/batteries8040031.

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Electric vehicles (EVs) and hybrid vehicles (HEVs) are being increasingly utilized for various reasons. The main reasons for their implementation are that they consume less or do not consume fossil fuel (no carbon dioxide pollution) and do not cause sound pollution. However, this technology has some challenges, including complex and troublesome accurate state of health estimation, which is affected by different factors. According to the increase in electric and hybrid vehicles’ application, it is crucial to have a more accurate and reliable estimation of state of charge (SOC) and state of health (SOH) in different environmental conditions. This allows improving battery management system operation for optimal utilization of a battery pack in various operating conditions. This article proposes an approach to estimate battery capacity based on two parameters. First, a practical and straightforward method is introduced to assess the battery’s internal resistance, which is directly related to the battery’s remaining useful life. Second, the different least square algorithm is explored. Finally, a promising, practical, simple, accurate, and reliable technique is proposed to estimate battery capacity appropriately. The root mean square percentage error and the mean absolute percentage error of the proposed methods were calculated and were less than 0.02%. It was concluded the geometry method has all the advantages of a recursive manner, including a fading memory, a close form of a solution, and being applicable in embedded systems.

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Nasreldin, Mohamed, Roger Delattre, Marc Ramuz, Cyril Lahuec, Thierry Djenizian, and Jean-Louis de Bougrenet de la Tocnaye. "Flexible Micro-Battery for Powering Smart Contact Lens." Sensors 19, no. 9 (May 3, 2019): 2062. http://dx.doi.org/10.3390/s19092062.

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In this paper, we demonstrate the first attempt of encapsulating a flexible micro battery into a contact lens to implement an eye-tracker. The paper discusses how to scale the battery to power various circuits embedded in the contact lens, such as ASIC, photodiodes, etc., as well as how to combine the battery with external harvested energy sources. The fabricated ring battery has a surface area of 0.75 cm2 yielding an areal capacity of 43 µAh·cm−2 at 20C. Based on simulated 0.35-µm CMOS ASIC power consumption, this value is large enough to allow powering the ASIC for 3 minutes. The functioning of the micro battery is demonstrated by powering an orange LED.

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Zhu, Minshen, Zhenguang Wang, Hongfei Li, Yuan Xiong, Zhuoxin Liu, Zijie Tang, Yang Huang, Andrey L. Rogach, and Chunyi Zhi. "Light-permeable, photoluminescent microbatteries embedded in the color filter of a screen." Energy & Environmental Science 11, no. 9 (2018): 2414–22. http://dx.doi.org/10.1039/c8ee00590g.

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Um, Ji Hyun, Seung-Ho Yu, Yong-Hun Cho, and Yung-Eun Sung. "SnO2 nanotube arrays embedded in a carbon layer for high-performance lithium-ion battery applications." New Journal of Chemistry 39, no. 4 (2015): 2541–46. http://dx.doi.org/10.1039/c4nj01958j.

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Cheng, Wei. "The Research of the Power Supply System of Embedded Portable Devices." Applied Mechanics and Materials 127 (October 2011): 496–500. http://dx.doi.org/10.4028/www.scientific.net/amm.127.496.

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Portable devices are mostly powered by battery. With the products tending to the direction of light, thin, short and multi-functional integration, the power requirements of portable devices are increasing all the time, but the energy density of battery is far behind the speed, the improvement of performance relies heavily on the power management technology. Therefore, it’s needed that manage the power of whole system with the integrated viewpoint to reduce power consumption and extend the system work time. After the analysis and research for power management technologies, one kind of a combination of hardware and software power management solution is proposed. The power management IC with embedded Linux operating system's Dynamic Power Management technology, better to reduce system power consumption, meets the requirements of the power system supplied by portable equipment.

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Gulsoy, B., T. A. Vincent, J. E. H. Sansom, and J. Marco. "In-situ temperature monitoring of a lithium-ion battery using an embedded thermocouple for smart battery applications." Journal of Energy Storage 54 (October 2022): 105260. http://dx.doi.org/10.1016/j.est.2022.105260.

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da Silva, Cynthia Thamires, Bruno Martin de Alcântara Dias, Rui Esteves Araújo, Eduardo Lorenzetti Pellini, and Armando Antônio Maria Laganá. "Two-Outputs Nonlinear Grey Box Model for Lithium-Ion Batteries." Energies 16, no. 5 (February 24, 2023): 2218. http://dx.doi.org/10.3390/en16052218.

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Storing energy efficiently is one of the main factors of a more sustainable world. The battey management system in energy storage plays an extremely important role in ensuring these systems’ efficiency, safety, and performance. This battery management system is capable of estimating the battery states, which are used to give better efficiency, a long life cycle, and safety. However, these states cannot be measured directly and must be estimated indirectly using battery models. Therefore, accurate battery models are essential for battery management systems implementation. One of these models is the nonlinear grey box model, which is easy to implement in embedded systems and has good accuracy when used with a good parameter identification method. Regarding the parameter identification methods, the nonlinear least square optimization is the most used method. However, to have accurate results, it is necessary to define the system’s initial states, which is not an easy task. This paper presents a two-outputs nonlinear grey box battery model. The first output is the battery voltage, and the second output is the battery state of charge. The second output was added to improve the system’s initial states identification and consequently improve the identified parameter accuracy. The model was estimated with the best experiment design, which was defined considering a comparison between seven different experiment designs regarding the fit to validation data, the parameter standard deviation, and the output variance. This paper also presents a method for defining a weight between the outputs, considering a greater weight in the output with greater model confidence. With this approach, it was possible to reach a value 1000 times smaller in the parameter standard deviation with a non-biased and little model prediction error when compared to the commonly used one-output nonlinear grey box model.

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Namdari, Alireza, Maryam Asad Samani, and Tariq S. Durrani. "Lithium-Ion Battery Prognostics through Reinforcement Learning Based on Entropy Measures." Algorithms 15, no. 11 (October 24, 2022): 393. http://dx.doi.org/10.3390/a15110393.

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Lithium-ion is a progressive battery technology that has been used in vastly different electrical systems. Failure of the battery can lead to failure in the entire system where the battery is embedded and cause irreversible damage. To avoid probable damages, research is actively conducted, and data-driven methods are proposed, based on prognostics and health management (PHM) systems. PHM can use multiple time-scale data and stored information from battery capacities over several cycles to determine the battery state of health (SOH) and its remaining useful life (RUL). This results in battery safety, stability, reliability, and longer lifetime. In this paper, we propose different data-driven approaches to battery prognostics that rely on: Long Short-Term Memory (LSTM), Autoregressive Integrated Moving Average (ARIMA), and Reinforcement Learning (RL) based on the permutation entropy of battery voltage sequences at each cycle, since they take into account vital information from past data and result in high accuracy.

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Han, Meisheng, Zijia Lin, and Jie Yu. "Ultrathin MoS2 nanosheets homogenously embedded in a N,O-codoped carbon matrix for high-performance lithium and sodium storage." Journal of Materials Chemistry A 7, no. 9 (2019): 4804–12. http://dx.doi.org/10.1039/c8ta10880c.

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Yu, Yue, Yuqi Liu, Xiaolei Peng, Xianchun Liu, Yan Xing, and Shuangxi Xing. "A multi-shelled CeO2/Co@N-doped hollow carbon microsphere as a trifunctional electrocatalyst for a rechargeable zinc–air battery and overall water splitting." Sustainable Energy & Fuels 4, no. 10 (2020): 5156–64. http://dx.doi.org/10.1039/d0se00735h.

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Kim, Da-Som, Sang-Yeon Kim, Kyung-Soo Kang, and Chung-Wook Roh. "Boost Converter Embedded Battery Charging Function for Application of E-bike." Transactions of the Korean Institute of Power Electronics 21, no. 2 (April 20, 2016): 175–81. http://dx.doi.org/10.6113/tkpe.2016.21.2.175.

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