scholarly journals Implementation of ABMS with Cuk Converter for Enhanced Battery Life using Internet of Things

Author(s):  
Juhi Jasiha E & Dr Rajeswari R

This paper describes about implementing absolute battery monitoring system using IoT (Internet of things) for enhanced battery life of BFEV. Cuk converter is used to give ripple less voltage to the battery and also the converter operates in both normal and regenerating modes. The converter is designed as Vs=20V, fs=50kHz with 80% of duty cycle for a 12V battery. For enhanced battery life, proper battery monitoring is important to analyze the battery performance. For SOC determination of battery, voltage method is used to identify the battery status by Proteus simulation software. The main aim is to analyze the sensitivity of the electrochemical model parameters under a real-world driving cycle for not only the terminal voltage, but also the essential states in an ABMS including the smart alerting and notification system through SMS using SIMCOM GSM modem in order to intimate the user regarding the battery level status.

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4034
Author(s):  
Arie Haenel ◽  
Yoram Haddad ◽  
Maryline Laurent ◽  
Zonghua Zhang

The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life.


2005 ◽  
Vol 43 (sup1) ◽  
pp. 253-266 ◽  
Author(s):  
J. A. Cabrera ◽  
A. Ortiz ◽  
E. Carabias ◽  
A. Simón

Modelling ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 259-287
Author(s):  
Robert Franke-Lang ◽  
Julia Kowal

The electrification of the powertrain requires enhanced performance of lithium-ion batteries, mainly in terms of energy and power density. They can be improved by optimising the positive electrode, i.e., by changing their size, composition or morphology. Thick electrodes increase the gravimetric energy density but generally have an inefficient performance. This work presents a 2D modelling approach for better understanding the design parameters of a thick LiFePO4 electrode based on the P2D model and discusses it with common literature values. With a superior macrostructure providing a vertical transport channel for lithium ions, a simple approach could be developed to find the best electrode structure in terms of macro- and microstructure for currents up to 4C. The thicker the electrode, the more important are the direct and valid transport paths within the entire porous electrode structure. On a smaller scale, particle size, binder content, porosity and tortuosity were identified as very impactful parameters, and they can all be attributed to the microstructure. Both in modelling and electrode optimisation of lithium-ion batteries, knowledge of the real microstructure is essential as the cross-validation of a cellular and lamellar freeze-casted electrode has shown. A procedure was presented that uses the parametric study when few model parameters are known.


2014 ◽  
Vol 556-562 ◽  
pp. 294-301 ◽  
Author(s):  
Long Han ◽  
Chun Tian ◽  
Yan Wang ◽  
Meng Ling Wu ◽  
Zhuo Jun Luo

This paper deals with the problem of braking process modeling. A subway train braking process simulation software is built, which composes of a GUI and a underlying model. The underlying model consists of a train model and a brake system model. The train model is simplified and built by assembling subcomponent element models of a railway vehicle. The brake system model is simplified and built based on experimental data in order to reduce computational effort. The GUI of the software can be use to input model parameters, display simulation results, and store simulation data. As a result of the simplifications of the modeling process, the developed software can perform real time simulation.


Author(s):  
Diane L. Stewart ◽  
Anthony J. Gerbino ◽  
Tony Scribner

A 38 MMSCF/D Cooper Bessemer Model LM-9 reciprocating compressor in hydrogen service at the Praxair Westlake LA facility has experienced notable particulate contamination within the feed gas. The particulates were believed to be caused by upstream piping corrosion; however, to definitely state the cause, the properties of the fluid existing in the five-stage compressor needed to be more fully understood. An OLI electrochemical simulation software was used for dew point prediction, determination of the condensed phase ionic equilibria, and corrosion rate prediction. These tasks were beyond capabilities of the site-licensed UniSim software, as presently configured. Specifically, the model was used to identify the dew point conditions (temperature, pressure) and properties of the condensed water (pH, corrosivity, dissolved O2, and chlorine speciation). Model results were compared with site inspection findings. Subsequently, recommended limits for chlorine and oxygen in the feed gas were established to improve long term compressor reliability.


2018 ◽  
Vol 612 ◽  
pp. A70 ◽  
Author(s):  
J. Olivares ◽  
E. Moraux ◽  
L. M. Sarro ◽  
H. Bouy ◽  
A. Berihuete ◽  
...  

Context. Membership analyses of the DANCe and Tycho + DANCe data sets provide the largest and least contaminated sample of Pleiades candidate members to date. Aims. We aim at reassessing the different proposals for the number surface density of the Pleiades in the light of the new and most complete list of candidate members, and inferring the parameters of the most adequate model. Methods. We compute the Bayesian evidence and Bayes Factors for variations of the classical radial models. These include elliptical symmetry, and luminosity segregation. As a by-product of the model comparison, we obtain posterior distributions for each set of model parameters. Results. We find that the model comparison results depend on the spatial extent of the region used for the analysis. For a circle of 11.5 parsecs around the cluster centre (the most homogeneous and complete region), we find no compelling reason to abandon King’s model, although the Generalised King model introduced here has slightly better fitting properties. Furthermore, we find strong evidence against radially symmetric models when compared to the elliptic extensions. Finally, we find that including mass segregation in the form of luminosity segregation in the J band is strongly supported in all our models. Conclusions. We have put the question of the projected spatial distribution of the Pleiades cluster on a solid probabilistic framework, and inferred its properties using the most exhaustive and least contaminated list of Pleiades candidate members available to date. Our results suggest however that this sample may still lack about 20% of the expected number of cluster members. Therefore, this study should be revised when the completeness and homogeneity of the data can be extended beyond the 11.5 parsecs limit. Such a study will allow for more precise determination of the Pleiades spatial distribution, its tidal radius, ellipticity, number of objects and total mass.


2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Caibing Liu ◽  
Fang Li ◽  
Guohao Chen ◽  
Xin Huang

With the integration of new technologies such as smart technologies and cloud computing in the industrial Internet of Things, the complexity of industrial IoT applications is increasing. Real-time performance and determinism are becoming serious challenges for system implementation in these Internet of Things systems, especially in critical security areas. This paper provides a framework for a software-defined bus-based intelligent robot system and designs scheduling algorithms to make TTEthernet play the role of scheduling in the framework. Through the framework, the non-real-time and uncertainties problem of distributed robotic systems can be solved. Moreover, a fragment strategy was proposed to solve the problem of large delay caused by Rate-Constrained traffic. Experimental results indicate that the improved scheme based on fragmentation strategy proposed in this paper can improve the real-time performance of RC traffic to a certain extent. Besides, this paper made a performance test and comparison experiments of the improved scheme in the simulation software to verify the feasibility of the improved scheme. The result showed that the delay of Rate-Constrained traffic was reduced and the utilization rate of network was improved.


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