Search results for: battery grading algorithm

Authors: S. K. Mohapatra, K. Ramanujam, S. Sankararaman

Abstract:

Redox flow battery (RFB) is a preferred energy storage option for grid stabilisation and energy arbitrage as it offers energy and power decoupling. In contrast to aqueous RFBs (ARFBs), nonaqueous RFBs (NARFBs) could offer high energy densities due to the wider electrochemical window of the solvents used, which could handle high and low voltage organic redox couples without undergoing electrolysis. In this study, a RFB based on benzyl viologen hexafluorophosphate [BV(PF6)2] as anolyte and N-hexyl phenothiazine [HPT] as catholyte demonstrated. A cell operated with mixed electrolyte (1:1) containing 0.2 M [BV(PF₆)₂] and 0.2 M [HPT] delivered a coulombic efficiency (CE) of 95.3 % and energy efficiency (EE) 53%, with nearly 68.9% material utilisation at 40 mA cm-2 current density.

Keywords: non-aqueous redox flow battery, benzyl viologen, N-hexyl phenothiazine, mixed electrolyte

Procedia PDF Downloads 51

Authors: Nassiri Khalid, El Hibaoui Abdelaaziz et Hajar Moha

Abstract:

In this paper, we introduce and analyse a probabilistic distributed algorithm for a construction of a minimum spanning tree on network. This algorithm is based on the handshake concept. Firstly, each network node is considered as a sub-spanning tree. And at each round of the execution of our algorithm, a sub-spanning trees are merged. The execution continues until all sub-spanning trees are merged into one. We analyze this algorithm by a stochastic process.

Keywords: Spanning tree, Distributed Algorithm, Handshake Algorithm, Matching, Probabilistic Analysis

Procedia PDF Downloads 631

Authors: S. Sharan Sundar, Nithish B. Moudhgalya, Nidhi Bhandari, Vineeth Vijayaraghavan

Abstract:

Automatic Short Answer Grading is one of the prime applications of artificial intelligence in education. Several approaches involving the utilization of selective handcrafted features, graphical matching techniques, concept identification and mapping, complex deep frameworks, sentence embeddings, etc. have been explored over the years. However, keeping in mind the real-world application of the task, these solutions present a slight overhead in terms of computations and resources in achieving high performances. In this work, a simple and effective solution making use of elemental features based on statistical, linguistic properties, and word-based similarity measures in conjunction with tree-based classifiers and regressors is proposed. The results for classification tasks show improvements ranging from 1%-30%, while the regression task shows a stark improvement of 35%. The authors attribute these improvements to the addition of multiple similarity scores to provide ensemble of scoring criteria to the models. The authors also believe the work could reinstate that classical natural language processing techniques and simple machine learning models can be used to achieve high results for short answer grading.

Keywords: artificial intelligence, intelligent systems, natural language processing, text mining

Procedia PDF Downloads 113

Authors: Yongkui Cui, Fengping Wang, Hailei Zhao, Muhammad Zubair Iqbal, Ziya Wang, Yan Li, Pengpeng LV

Abstract:

The novel 3D SnO cabbages self-assembled by nanosheets were successfully synthesized via template-free hydrothermal growth method under facile conditions.The XRD results manifest that the as-prepared SnO is tetragonal phase. The TEM and HRTEM results show that the cabbage nanosheets are polycrystalline structure consisted of considerable single-crystalline nanoparticles. Two typical Raman modes A1g=210 and Eg=112 cm-1 of SnO are observed by Raman spectroscopy. Moreover, galvanostatic cycling tests has been performed using the SnO cabbages as anode material of lithium ion battery and the electrochemical results suggest that the synthesized SnO cabbage structures are a promising anode material for lithium ion batteries.

Keywords: electrochemical property, hydrothermal synthesis, lithium ion battery, stannous oxide

Procedia PDF Downloads 430

Authors: Farhan Beg

Abstract:

This paper presents a method for the efficient implementation of a unidirectional or bidirectional DC/DC converter. The DC/DC converter is used essentially for energy exchange between the low voltage service battery and a high voltage battery commonly found in Electric Vehicle applications. In these applications, apart from cost, efficiency of design is an important characteristic. A useful way to reduce the size of electronic equipment in the electric vehicles is proposed in this paper. The technique simplifies the mechanical complexity and maximizes the energy usage using the latest converter control techniques. Moreover a bidirectional battery charger for hybrid electric vehicles is also implemented in this paper. Several simulations on the test system have been carried out in Matlab/Simulink environment. The results exemplify the robustness of the proposed design methodology in case of a 1.5 KW DC-DC converter.

Keywords: DC-DC converters, electric vehicles, power electronics, direct current control

Procedia PDF Downloads 694

Authors: Asmir Gogic, Aljo Mujcic, Sandra Ibric, Nermin Suljanovic

Abstract:

Ubiquity of natural disasters during last few decades have risen serious questions towards the prediction of such events and human safety. Every disaster regardless its proportion has a precursor which is manifested as a disruption of some environmental parameter such as temperature, humidity, pressure, vibrations and etc. In order to anticipate and monitor those changes, in this paper we propose an overall system for disaster prediction and monitoring, based on wireless sensor network (WSN). Furthermore, we introduce a modified and simplified WSN routing protocol built on the top of the trickle routing algorithm. Routing algorithm was deployed using the bluetooth low energy protocol in order to achieve low power consumption. Performance of the WSN network was analyzed using a real life system implementation. Estimates of the WSN parameters such as battery life time, network size and packet delay are determined. Based on the performance of the WSN network, proposed system can be utilized for disaster monitoring and prediction due to its low power profile and mesh routing feature.

Keywords: bluetooth low energy, disaster prediction, mesh routing protocols, wireless sensor networks

Procedia PDF Downloads 356

Authors: Jaejin Han, Jinsub Choi

Abstract:

Vanadium redox flow battery (VRFB) is a type of redox flow battery which uses vanadium ionic solution as electrolyte. Inside the VRFB, 2.5mm thickness of graphite is generally used as bipolar plate for anti-corrosion of current collector. In this research, thick graphite bipolar plate was substituted by 0.126mm thickness of dimensionally stable anode which was coated with IrO2 on an anodic nanotubular TiO2 substrate. It can provide dimensional advantage over the conventional graphite when the VRFB is used as multi-stack. Ir was coated by using spray coating method in order to enhance electric conductivity. In this study, various electrochemical characterizations were carried out. Cyclic voltammetry data showed activation of Ir in the positive electrode of VRFB. In addition, polarization measurements showed Ir-coated DSA had low overpotential in the positive electrode of VRFB. In cell test results, the DSA-used VRFB showed better efficiency than graphite-used VRFB in voltage and overall efficiency.

Keywords: bipolar plate, DSA (dimensionally stable anode), iridium oxide coating, TiO2 nanotubes, VRFB (vanadium redox flow battery)

Procedia PDF Downloads 464

Authors: P. R. Dushantha Chaminda, Peng Kai

Abstract:

In this review paper, we enclose the thought of wireless ad hoc networks and particularly mobile ad hoc network (MANET), their field of study, intention, concern, benefit and disadvantages, modifications, with relation of AODV routing protocol. Mobile computing is developing speedily with progression in wireless communications and wireless networking protocols. Making communication easy, we function most wireless network devices and sensor networks, movable, battery-powered, thus control on a highly constrained energy budget. However, progress in battery technology presents that only little improvements in battery volume can be expected in the near future. Moreover, recharging or substitution batteries is costly or unworkable, it is preferable to support energy waste level of devices low.

Keywords: wireless ad hoc network, energy efficient routing protocols, AODV, EOAODV, AODVEA, AODVM, AOMDV, FF-AOMDV, AOMR-LM

Procedia PDF Downloads 185

Authors: Zhihong Luo, Guangbin Zhu, Lulu Guo, Zhujun Lyu, Kun Luo

Abstract:

Cycling life has become the threshold for the prospective application of Li-O₂ batteries, and the protection of Li anode has recently regarded as the key factor to the performance. Herein, a simple low rate pre-activation (20 cycles at 0.5 Ag⁻¹ and a capacity of 200 mAh g⁻¹) was employed to effectively improve the performance and cyclability of Li-O₂ batteries. The charge/discharge cycles at 1 A g⁻¹ with a capacity of 1000 mAh g⁻¹ were maintained for up to 290 times versus 55 times for the cell without pre-activation. The ultimate battery capacity and high rate discharge property were also largely enhanced. Morphology, XRD and XPS analyses reveal that the performance improvement is in close association with the formation of the smooth and compact surface layer formed on the Li anode after low rate pre-activation, which apparently alleviated the corrosion of Li anode and the passivation of cathode during battery cycling, and the corresponding mechanism was also discussed.

Keywords: lithium oxygen battery, pre-activation, cyclability, capacity

Procedia PDF Downloads 124

Authors: Jeong-Hyun Yoo, Hanjung Kwon, Sung-Wook Cho

Abstract:

Fused salt electrolysis was studied to make the high purity rare-earth metals using domestic rare-earth ore. The target metals of the fused salt electrolysis were Mm (Misch metal), La, Ce, Nd, etc. Fused salt electrolysis was performed with the supporting salt such as chloride and fluoride at the various temperatures and ampere. The metals made by fused salt electrolysis were analyzed to identify the phase and composition using the methods of XRD and ICP. As a result, the acquired rare-earth metals were the high purity ones which had more than 99% purity. Also, VIM (vacuum induction melting) was studied to make the kg level rare-earth alloy for the use of secondary battery and hydrogen storage. In order to indentify the physicochemical properties such as phase, impurity gas, alloy composition and hydrogen storage, the alloys were investigated. The battery characteristics were also analyzed through the various tests in the real production line of a battery company.

Keywords: domestic rare-earth ore, fused salt electrolysis, rare-earth materials, hydrogen storage alloy, secondary battery

Procedia PDF Downloads 499

Authors: Asep Andi Suryandi, Katri Yulianto, Dewi Rianti Mandasari

Abstract:

The development of environmentally friendly vehicles increasingly attracted the attention of almost all countries in the world, including Indonesia. There are various types of environmentally friendly vehicles, such as: electric vehicles, hybrid, and fuel gas. The Electric vehicle has been developed in Indonesia, a private or public vehicle. But many electric vehicles had been developed using the battery as a power source, while the battery technology for electric vehicles still constraints in capacity, dimensions of the battery itself and charging system. Trolley bus is one of the electric buses with the main power source of the network catenary / overhead line with trolley pole as the point of contact. This paper will discuss the design and manufacture electrical system in Trolleybus.

Keywords: trolley bus, electric propulsion system, design, manufacture, electric vehicle

Procedia PDF Downloads 320

Authors: Shaharuddin Salleh, Sara Marouf, Hosein Mohammadi

Abstract:

Directional sensor networks (DSNs) have recently attracted a great deal of attention due to their extensive applications in a wide range of situations. One of the most important problems associated with DSNs is covering a set of targets in a given area and, at the same time, maximizing the network lifetime. This is due to limitation in sensing angle and battery power of the directional sensors. This problem gets more complicated by the possibility that targets may have different coverage requirements. In the present study, this problem is referred to as priority-based target coverage (PTC). As sensors are often densely deployed, organizing the sensors into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set could satisfy coverage requirements of all the targets. Several experiments are conducted to evaluate the performance of the proposed algorithm. The results demonstrated that the algorithms were able to contribute to solving the problem.

Keywords: directional sensor networks, target coverage problem, cover set formation, learning automata

Procedia PDF Downloads 384

Authors: Atef Y. Shenouda, Anton A. Momchilov

Abstract:

Graphene and CdO with different stoichiometric ratios of Cd(CH₃COO)₂ and graphene samples were prepared by hydrothermal reaction. The crystalline phases of pure CdO and 3CdO:1graphene were identified by X-ray diffraction (XRD). The particle morphology was studied with SEM. Furthermore, impedance measurements were applied. Galvanostatic measurements for the cells were carried out using potential limits between 0.01 and 3 V vs. Li/Li⁺. The current cycling intensity was 10⁻⁴ A. The specific discharge capacity of 3CdO-1G cell was about 450 Ah.Kg⁻¹ up to more than 100 cycles.

Keywords: CdO, graphene, negative electrode, lithium battery

Procedia PDF Downloads 124

Authors: Iqra Yaseen

Abstract:

One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

Procedia PDF Downloads 66

Authors: Y. Ghiassi-Farrokhfal

Abstract:

The number of electric vehicles (EVs) is increasing worldwide. Replacing gas fueled cars with EVs reduces carbon emission. However, the extensive energy consumption of EVs stresses the energy systems, requiring non-green sources of energy (such as gas turbines) to compensate for the new energy demand caused by EVs in the energy systems. To make EVs even a greener solution for the future energy systems, new EV charging stations are equipped with solar PV panels and batteries. This will help serve the energy demand of EVs through the green energy of solar panels. To ensure energy availability, solar panels are combined with batteries. The energy surplus at any point is stored in batteries and is used when there is not enough solar energy to serve the demand. While EV charging stations equipped with solar panels and batteries are green and ecologically optimal, they might not be financially viable solutions, due to battery prices. To make the system viable, we should size the battery economically and operate the system optimally. This is, in general, a challenging problem because of the stochastic nature of the EV arrivals at the charging station, the available solar energy, and the battery operating system. In this work, we provide a mathematical model for this problem and we compute the return on investment (ROI) of such a system, which is designed to be ecologically and financially optimal. We also quantify the minimum required investment in terms of battery and solar panels along with the operating strategy to ensure that a charging station has enough energy to serve its EV demand at any time.

Keywords: solar energy, battery storage, electric vehicle, charging stations

Procedia PDF Downloads 194

Authors: Vishnu Pratap Singh Kirar

Abstract:

Artificial Neural Network (ANN) can be trained using backpropagation (BP). It is the most widely used algorithm for supervised learning with multi-layered feed-forward networks. Efficient learning by the BP algorithm is required for many practical applications. The BP algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a two-term algorithm consisting of a learning rate (LR) and a momentum factor (MF). The major drawbacks of the two-term BP learning algorithm are the problems of local minima and slow convergence speeds, which limit the scope for real-time applications. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and criteria for evaluating convergence are required to facilitate the application of the three terms BP algorithm. Although these two seem to be closely related, as described later, we summarize various improvements to overcome the drawbacks. Here we compare the different methods of convergence of the new three-term BP algorithm.

Keywords: neural network, backpropagation, local minima, fast convergence rate

Procedia PDF Downloads 468

Authors: Yifu Ding, Vijay Avinash, Malcolm McCulloch

Abstract:

As the proliferation of decentralized energy systems, the UK power system allows small-scale entities such as microgrids (MGs) to tender multiple energy services including energy arbitrage and frequency responses (FRs). However, its operation requires the balance between the uncertain renewable generations and loads in real-time and has to fulfill their provision requirements of contract services continuously during the time window agreed, otherwise it will be penalized for the under-delivered provision. To hedge against risks due to uncertainties and maximize the economic benefits, we propose a stochastic model predictive control (SMPC) framework to optimize its operation for the multi-service provision. Distinguished from previous works, we include a detailed economic-degradation model of the lithium-ion battery to quantify the costs of different service provisions, as well as accurately describe the changing dynamics of the battery. Considering a branch of load and generation scenarios and the battery aging, we formulate a risk-averse cost function using conditional value at risk (CVaR). It aims to achieve the maximum expected net revenue and avoids severe losses. The framework will be performed on a case study of a PV-battery grid-tied microgrid in the UK with real-life data. To highlight its performance, the framework will be compared with the case without the degradation model and the deterministic formulation.

Keywords: model predictive control (MPC), battery degradation, frequency response, microgrids

Procedia PDF Downloads 101

Authors: Kevin Worrall, Euan McGookin

Abstract:

The use of optimization algorithms is common across a large number of diverse fields. This work presents the use of a hybrid optimization algorithm applied to a mobile robot tasked with carrying out a search of an unknown environment. The algorithm is then applied to the multiple robots case, which results in a reduction in the time taken to carry out the search. The hybrid algorithm is a Random Search Algorithm fused with a Tabu mechanism. The work shows that the algorithm locates the desired points in a quicker time than a brute force search. The Tabu Random algorithm is shown to work within a simulated environment using a validated mathematical model. The simulation was run using three different environments with varying numbers of targets. As an algorithm, the Tabu Random is small, clear and can be implemented with minimal resources. The power of the algorithm is the speed at which it locates points of interest and the robustness to the number of robots involved. The number of robots can vary with no changes to the algorithm resulting in a flexible algorithm.

Keywords: algorithms, control, multi-agent, search and rescue

Procedia PDF Downloads 214

Authors: Thirupathi Thippani, Kothandaraman Ramanujam

Abstract:

Current research on energy storage has been paid to metal-air batteries, because of attractive alternate energy source for the future. Metal – air batteries have the probability to significantly increase the power density, decrease the cost of energy storage and also used for a long time due to its high energy density, low-level pollution, light weight. The performance of these batteries mostly restricted by the slow kinetics of the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) on cathode during battery discharge and charge. The ORR and OER are conventionally carried out with precious metals (such as Pt) and metal oxides (such as RuO₂ and IrO₂) as catalysts separately. However, these metal-based catalysts are regularly undergoing some difficulties, including high cost, low selectivity, poor stability and unfavorable to environmental effects. So, in order to develop the active, stable, corrosion resistance and inexpensive bi-functional catalyst material is mandatory for the commercialization of zinc-air rechargeable battery technology. We have attempted and synthesized non-precious metal (NPM) catalysts comprising cobalt and N-doped multiwalled carbon nanotubes (N-MWCNTs-Co) were synthesized by the solid-state pyrolysis (SSP) of melamine with Co₃O₄. N-MWCNTs-Co acts as an excellent electrocatalyst for both the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER), and hence can be used in secondary metal-air batteries and in unitized regenerative fuel cells. It is important to study the OER and ORR at high concentrations of KOH as most of the metal-air batteries employ KOH concentrations > 4M. In the first 16 cycles of the zinc-air battery while using N-MWCNTs-Co, 20 wt.% Pt/C or 20 wt.% IrO₂/C as air electrodes. In the ORR regime (the discharge profile of the zinc-air battery), the cell voltage exhibited by N-MWCNTs-Co was 44 and 83 mV higher (based on 5th cycle) in comparison to of 20 wt.% Pt/C and 20 wt.% IrO₂/C respectively. To demonstrate this promise, a zinc-air battery was assembled and tested at a current density of 0.5 Ag⁻¹ for charge-discharge 100 cycles.

Keywords: oxygen reduction reaction (ORR), oxygen evolution reaction(OER), non-platinum, zinc air battery

Procedia PDF Downloads 205

Authors: Amogh Katti, J. Sai Asritha, D. Nivedh, M. Kalyan Srinivas, B. Somnath Chakravarthi

Abstract:

Today's modern education system uses Learning Management System (LMS) portals for the scoring and grading of student performances, to maintain student records, and teachers are instructed to accept assignments through online submissions of .pdf,.doc,.ppt, etc. There is a risk of data tampering in the traditional portals; we will apply the Blockchain model instead of this traditional model to avoid data tampering and also provide a decentralized mechanism for overall fairness. Blockchain technology is a better and also recommended model because of the following features: consensus mechanism, decentralized system, cryptographic encryption, smart contracts, Ethereum blockchain. The proposed system ensures data integrity and tamper-proof assignment submission and grading, which will be helpful for both students and also educators.

Keywords: education technology, learning management system, decentralized applications, blockchain

Procedia PDF Downloads 47

Authors: Harikrishna Yadav Nanganuru, Narasimhulu Korrapati

Abstract:

Over the past many years, many sites in the world have been contaminated with heavy metals, which are the largest class of contaminants. Lead is one of the toxic heavy metals contaminated in the environment. Lead is not biodegradable, that’s why it is accumulated in the human body and impacts all the systems of the human body when it has been taken by humans. The accumulation of lead in the water environment has been showing adverse effects on the public health. So the removal of lead from the water environment by the biosorption process, which is emerged as a potential method for the lead removal, is an efficient approach. This work was focused to examine the removal of Lead [Pb (II)] ions from aqueous solution and effluent from battery industry. Lead contamination in water is a widespread problem throughout the world and mainly results from lead acid battery manufacturing effluent. In this work, isolated bacteria from wastewater of lead acid battery industry has been utilized for the removal of lead. First effluent from the lead acid battery industry was characterized by the inductively coupled plasma atomic emission spectrometry (ICP – AES). Then the bacteria was isolated from the effluent and used it’s immobilized dead mass for the biosorption of lead. Scanning electron microscopic (SEM) and Atomic force microscopy (AFM) studies clearly suggested that the Lead (Pb) was adsorbed efficiently. The adsorbed percentage of lead (II) from waste was 97.40 the concentration of lead (II) is measured by Atomic Absorption Spectroscopy (AAS). From the result of AAS it can be concluded that immobilized isolated dead mass was well efficient and useful for biosorption of lead contaminated waste water.

Keywords: biosorption, ICP-AES, lead (Pb), SEM

Procedia PDF Downloads 355

Authors: Mohammad Rostami, Mohammad Reza Forghani, Elahe Neshat, Fatemeh Yaghoobi

Abstract:

An Ad Hoc network consists of wireless mobile equipment which connects to each other without any infrastructure, using connection equipment. The best way to form a hierarchical structure is clustering. Various methods of clustering can form more stable clusters according to nodes' mobility. In this research we propose an algorithm, which allocates some weight to nodes based on factors, i.e. link stability and power reduction rate. According to the allocated weight in the previous phase, the cellular learning automaton picks out in the second phase nodes which are candidates for being cluster head. In the third phase, learning automaton selects cluster head nodes, member nodes and forms the cluster. Thus, this automaton does the learning from the setting and can form optimized clusters in terms of power consumption and link stability. To simulate the proposed algorithm we have used omnet++4.2.2. Simulation results indicate that newly formed clusters have a longer lifetime than previous algorithms and decrease strongly network overload by reducing update rate.

Keywords: mobile Ad Hoc networks, clustering, learning automaton, cellular automaton, battery power

Procedia PDF Downloads 377

Authors: Muhammad Affan, Muhammad Ilyas Raza, Muhammad Harris Hashmi

Abstract:

This work is attributed to the battery management unit design of student Satellites under Pakistan National Student Satellite Program (PNSSP). The aim has been to design a customized, low-cost, efficient, reliable and less-complex battery management scheme for the Satellite. Nowadays, Lithium Ion (Li-ion) batteries have become the de-facto standard for remote applications, especially for satellites. Li-ion cells are selected for secondary storage. The design also addresses Li-ion safety requirements by monitoring, balancing and protecting cells for safe and prolonged operation. Accurate voltage measurement of individual cells was the main challenge because all the actions triggered were based on the digital voltage measurement. For this purpose, a resistive-divider network is used to maintain simplicity and cost-effectiveness. To cater the problem of insufficient i/o pins on microcontroller, fast multiplexers and de-multiplexers were used. The discrepancy inherited in the given design is the dissipation of heat due to the dissipative resistors. However, it is still considered to be the optimum adoption, considering the simple and cost-effective nature of the passive balancing technique. Furthermore, it is a completely unique solution, customized to meet specific requirements. However, there is still an option for a more advanced and expensive design.

Keywords: satellite, battery module, passive balancing, dissipative

Procedia PDF Downloads 94

Authors: Sangwoo Han, Saeed Khaleghi Rahimian, Ying Liu

Abstract:

Vehicle electrification is gaining momentum, and many car manufacturers promise to deliver more electric vehicle (EV) models to consumers in the coming years. In controlling the battery pack, the battery management system (BMS) must maintain optimal battery performance while ensuring the safety of a battery pack. Tasks related to battery performance include determining state-of-charge (SOC), state-of-power (SOP), state-of-health (SOH), cell balancing, and battery charging. Safety related functions include making sure cells operate within specified, static and dynamic voltage window and temperature range, derating power, detecting faulty cells, and warning the user if necessary. The BMS often utilizes an RC circuit model to model a Li-ion cell because of its robustness and low computation cost among other benefits. Because an equivalent circuit model such as the RC model is not a physics-based model, it can never be a prognostic model to predict battery state-of-health and avoid any safety risk even before it occurs. A physics-based Li-ion cell model, on the other hand, is more capable at the expense of computation cost. To avoid the high computation cost associated with a full-order model, many researchers have demonstrated the use of a single particle model (SPM) for BMS applications. One drawback associated with the single particle modeling approach is that it forces to use the average current density in the calculation. The SPM would be appropriate for simulating drive cycles where there is insufficient time to develop a significant current distribution within an electrode. However, under a continuous or high-pulse electrical load, the model may fail to predict cell voltage or Li⁺ plating potential. To overcome this issue, a multi-particle reduced-order model is proposed here. The use of multiple particles combined with either linear or nonlinear charge-transfer reaction kinetics enables to capture current density distribution within an electrode under any type of electrical load. To maintain computational complexity like that of an SPM, governing equations are solved sequentially to minimize iterative solving processes. Furthermore, the model is validated against a full-order model implemented in COMSOL Multiphysics.

Keywords: battery management system, physics-based li-ion cell model, reduced-order model, single-particle and multi-particle model

Procedia PDF Downloads 82

Authors: Thomas Yeboah

Abstract:

Cloud Computing is newly paradigm in computing that promises a delivery of computing as a service rather than a product, whereby shared resources, software, and information are provided to computers and other devices as a utility (like the electricity grid) over a network (typically the Internet). As Cloud Computing is a newly style of computing on the internet. It has many merits along with some crucial issues that need to be resolved in order to improve reliability of cloud environment. These issues are related with the load balancing, fault tolerance and different security issues in cloud environment.In this paper the main concern is to develop an effective load balancing algorithm that gives satisfactory performance to both, cloud users and providers. This proposed algorithm (hybrid Bee Ant Colony algorithm) is a combination of two dynamic algorithms: Ant Colony Optimization and Bees Life algorithm. Ant Colony algorithm is used in this hybrid Bee Ant Colony algorithm to solve load balancing issues whiles the Bees Life algorithm is used for optimization of job scheduling in cloud environment. The results of the proposed algorithm shows that the hybrid Bee Ant Colony algorithm outperforms the performances of both Ant Colony algorithm and Bees Life algorithm when evaluated the proposed algorithm performances in terms of Waiting time and Response time on a simulator called CloudSim.

Keywords: ant colony optimization algorithm, bees life algorithm, scheduling algorithm, performance, cloud computing, load balancing

Procedia PDF Downloads 596

Authors: Sardar Ameer Akram Khan, Shahzad Amin Sheikh

Abstract:

Blind equalization is an important technique amongst equalization family. Multimodulus algorithms based on blind equalization removes the undesirable effects of ISI and cater ups the phase issues, saving the cost of rotator at the receiver end. In this paper a new algorithm combination of recursive least square and Multimodulus algorithm named as RLSMMA is proposed by providing few assumption, fast convergence and minimum Mean Square Error (MSE) is achieved. The excellence of this technique is shown in the simulations presenting MSE plots and the resulting filter results.

Keywords: blind equalizations, constant modulus algorithm, multi-modulus algorithm, recursive least square algorithm, quadrature amplitude modulation (QAM)

Procedia PDF Downloads 617

Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

Abstract:

As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the Central Processing Unit (CPU), operational (RAM), and permanent (ROM) memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles

Procedia PDF Downloads 75

Authors: Safa Adi

Abstract:

This paper will consider the problem of sequential mining patterns embedded in a database by handling the time constraints as defined in the GSP algorithm (level wise algorithms). We will compare two previous approaches GTC and PSP, that resumes the general principles of GSP. Furthermore this paper will discuss PG-hybrid algorithm, that using PSP and GTC. The results show that PSP and GTC are more efficient than GSP. On the other hand, the GTC algorithm performs better than PSP. The PG-hybrid algorithm use PSP algorithm for the two first passes on the database, and GTC approach for the following scans. Experiments show that the hybrid approach is very efficient for short, frequent sequences.

Keywords: database, GTC algorithm, PSP algorithm, sequential patterns, time constraints

Procedia PDF Downloads 356

Authors: Ali Nourollah, Mohsen Movahedinejad

Abstract:

In this paper a new algorithm to generate random simple polygons from a given set of points in a two dimensional plane is designed. The proposed algorithm uses a genetic algorithm to generate polygons with few vertices. A new merge algorithm is presented which converts any two polygons into a simple polygon. This algorithm at first changes two polygons into a polygonal chain and then the polygonal chain is converted into a simple polygon. The process of converting a polygonal chain into a simple polygon is based on the removal of intersecting edges. The merge algorithm has the time complexity of O ((r+s) *l) where r and s are the size of merging polygons and l shows the number of intersecting edges removed from the polygonal chain. It will be shown that 1 < l < r+s. The experiments results show that the proposed algorithm has the ability to generate a great number of different simple polygons and has better performance in comparison to celebrated algorithms such as space partitioning and steady growth.

Keywords: Divide and conquer, genetic algorithm, merge polygons, Random simple polygon generation.

Procedia PDF Downloads 507

Authors: Foo Shen Hwang, Thomas Confrey, Stephen Scully, Barry Flannery

Abstract:

Thermal characterization plays an important role in battery pack design. Lithium-ion batteries have to be maintained between 15-35 °C to operate optimally. Heat is generated (Q) internally within the batteries during both the charging and discharging phases. This can be quantified using several standard methods. The most common method of calculating the batteries heat generation is through the addition of both the joule heating effects and the entropic changes across the battery. In addition, such values can be derived by identifying the open-circuit voltage (OCV), nominal voltage (V), operating current (I), battery temperature (T) and the rate of change of the open-circuit voltage in relation to temperature (dOCV/dT). This paper focuses on experimental characterization and comparative modelling of the heat generation rate (Q) across several current discharge rates (0.5C, 1C, and 1.5C) of a 18650 cell. The analysis is conducted utilizing several non-linear mathematical functions methods, including polynomial, exponential, and power models. Parameter fitting is carried out over the respective function orders; polynomial (n = 3~7), exponential (n = 2) and power function. The generated parameter fitting functions are then used as heat source functions in a 3-D computational fluid dynamics (CFD) solver under natural convection conditions. Generated temperature profiles are analyzed for errors based on experimental discharge tests, conducted at standard room temperature (25°C). Initial experimental results display low deviation between both experimental and CFD temperature plots. As such, the heat generation function formulated could be easier utilized for larger battery applications than other methods available.

Keywords: computational fluid dynamics, curve fitting, lithium-ion battery, voltage drop

Procedia PDF Downloads 65