Battery Capacity

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The Nonlinear Variable Selection and Its Realtime Detection of Lead-acid Battery Capacity

The Nonlinear Variable Selection and Its Realtime Detection of Lead-acid Battery Capacity

The capacity of Lead-acid storage battery can be predicted online by using the method of soft sensing, where the secondary variables should be screened with RReliefF method. It considers all the possible secondary variables first time. Then, compute the explanation ability of each secondary variable, whereas different kinds of secondary variables set are constructed according to weed out the poorest explanation ability of secondary variables in turn. After that, compared with the different accuracy of lead-acid storage battery capacity with testing data, the best streamlined soft sensing model is built up with BP neural network among on all the possible secondary variable sets. The method is expected to be extended in the production process quality monitoring research for a wide range of applications.

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Effectiveness Of Battery Capacity On Engine Performance

Effectiveness Of Battery Capacity On Engine Performance

Battery is the power source of a vehicle. The specifications of the battery is rarely known by people and they do not is the battery is compatible with the vehicle. Car users must choose the correct type of battery to their vehicles. Is this will affect the engine performance of the car? In this project, the effect of the battery capacity on the engine performance is analysed.

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Accelerated Reported Battery Capacity Loss in 30 kWh Variants of the Nissan Leaf

Accelerated Reported Battery Capacity Loss in 30 kWh Variants of the Nissan Leaf

decline over time) would result if a constant fraction of ions are immobilised in the batteries each year, in the way projected by Larsen (2016) for Leafs. Our observed pattern rejects this geometric model. Sharp downward inflections in battery health are expected in generalised battery health scenarios (Buchmann, 2014; Warnecke, 2017) and the technology applied to electric vehicles in general. Leafs, with their battery chemistries, have not been in place long enough to know if and 350

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Design and performance analysis of energy harvesting communications systems

Design and performance analysis of energy harvesting communications systems

Solar energy is certainly one of the most commonly used ambient energy, since light can be directly converted into electricity that runs a wide range of indoor and portable devices [HD88]. Also, solar energy is by far the largest and most available source among the renewable energy sources. In a communication network for example, the BS transmitter can be equipped with high solar panels that provide it with constant energy supply [CSAA16]. Solar energy is indeed a practical source for getting additional energy in outdoor networks. In wireless sensor networks for instance, intelligent solar energy harvesting systems comprised of solar panels and control circuits are highly beneficial [LS15]. RF energy harvesting, on the other hand, can be used in recharging a wireless node having limited battery capacity [PSZS13].

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DYNAMIC SENSOR RELOCATION TECHNIQUE BASED LIGHT WEIGHT INTEGRATED PROTOCOL FOR 
WSN

DYNAMIC SENSOR RELOCATION TECHNIQUE BASED LIGHT WEIGHT INTEGRATED PROTOCOL FOR WSN

the same level, each generation has the ability to supply power to the network. While in equal output power method, if there is large differences on the battery capacity, there will be a condition where the generation is running out of battery level, while other generation can not supply the load on that generation, due to the limited capacity of the inverter. In stand-alone mode, the power-sharing does not occur because each inverter work, supplying load power owned by each generation. Based on the performance parameters of each method, it can be concluded that the operation method of the microgrid based on equal battery level is still better than the stand alone method and equal output power method. In which, with equal battery level method obtained PDI = 100%, meanwhile in, equal output power PDI = 97, 92% and standalone modes obtained PDI = 96.33%. BCI value for equal battery level method obtained BCI = 100.00%, as same as that obtained using equal ouput power method and in standalone operation mode BCI = 98.02%.

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Transportation safety of lithium iron phosphate batteries   a feasibility study of storing at very low states of charge

Transportation safety of lithium iron phosphate batteries a feasibility study of storing at very low states of charge

Considering the challenges facing long-haul transportation of Li-ion batteries, in this paper we propose a proto- col whereby 99.1% of the battery’s energy is removed prior to shipping. We show that removing 99.1% of the total stored energy (0% SoC) of a Li-ion battery of LFP chemistry is safer than the current ICAO standard of 30% SoC for transportation in the event of short circuit. Using a novel dataset, it was shown that cells stored at such low SoC values did not exhibit significant irreversible capacity fade. While storing at very low voltages (≤0.5 V per cell) is ideal from an electrical hazard perspective, the results indicate, in agreement with previous literature, that SEI dissolution was more pronounced, leading to significant degradation of battery capacity (up-to 30% within 15 days). On the other hand, around 0% SoC was found to be a voltage stability window for the transportation of Li-ion batteries, which does not comprise the battery’s state of health.

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The  leaking  battery:  A  privacy  analysis  of  the  HTML5  Battery  Status  API

The leaking battery: A privacy analysis of the HTML5 Battery Status API

Abstract. We highlight privacy risks associated with the HTML5 Battery Status API. We put special focus on its implementation in the Firefox browser. Our study shows that websites can discover the capacity of users’ batteries by exploiting the high precision readouts provided by Firefox on Linux. The capacity of the battery, as well as its level, expose a fingerprintable surface that can be used to track web users in short time intervals. Our analysis shows that the risk is much higher for old or used batteries with reduced capacities, as the battery capacity may potentially serve as a tracking identifier. The fingerprintable surface of the API could be drastically reduced without any loss in the API’s functionality by reducing the precision of the readings. We propose minor modifications to Battery Status API and its implementation in the Firefox browser to address the privacy issues presented in the study. Our bug report for Firefox was accepted and a fix is deployed.

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A novel battery and super capacitor using IoT to interface renewable energy sources with dual direction and its application

A novel battery and super capacitor using IoT to interface renewable energy sources with dual direction and its application

Three port triple half scaffold bidirectional dc-dc converter is displayed in [4] that interface super capacitor, energy component and load. In any case it has just bidirectional port subsequently it doesn't bolster regenerative load. Half scaffold setup has of the converter has restrictions from the view purpose of energy rating, since high recurrence of current needs to go through the half extension capacitors in full. More finished because of wide working extent at the battery or super capacitor port limits the wide zero voltage exchanging (ZVS) run. Three port current bolstered full extension bidirectional converters which has the benefit of lessened current swell at the contribution because of the nearness of info inductor is introduced in [8]. The disadvantage of this topology is that it is reasonable just for low power and low yield voltage applications. In spite of the fact that the channel necessities are less it builds the control many-sided quality of the circuit.

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On line Estimation of Power Battery SOC Based on FPGA

On line Estimation of Power Battery SOC Based on FPGA

SOC (State of charge) is an important parameter to describe the charge and discharge capacity of the battery. It is of great significance to give full play to the performance of the battery system, improve the safety of the battery, prevent the overcharge and discharge of the battery, and prolong the life of the battery. Moreover, because of the use of batteries, the battery's SOC will change continuously, so the BMS with on-line monitoring ability, which can update the SOC parameters accurately and periodically, is far superior to the BMS without the real-time parameter update. Therefore, it is very important to design BMS with on-line SOC estimation function [2].

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Mobile Cloud Computing: World’s Leading
          Technology for Mobile Devices

Mobile Cloud Computing: World’s Leading Technology for Mobile Devices

Mobile devices allow users to run powerful applications that take advantage of the growing availability of built-in sensing and better data exchange capabilities of mobile devices. As a result, mobile applications seamlessly integrate with real time data streams and Web 2.0 applications, such as mashups, open collaboration, social networking and mobile commerce. The mobile execution platform is being used for more and more tasks, e.g., for playing games; capturing, editing, annotating and uploading video; handling finances; managing personal health, micro payments, ticket purchase, interacting with ubiquitous computing infrastructures. Even mobile device hardware and mobile networks continue to evolve and to improve, mobile devices will always be resource-poor, less secure, with unstable connectivity, and with less energy since they are powered by battery. Resource poverty is major obstacle for many applications. Therefore, computation on mobile devices will always involve a compromise. Mobile devices can be seen as entry points and interface of cloud online services. Recently, it has been discussed what cloud

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OPTIMAL SIZING OF HYBRID SYSTEM FOR STAND-ALONE APPLICATION USING GENETIC ALGORITHM

OPTIMAL SIZING OF HYBRID SYSTEM FOR STAND-ALONE APPLICATION USING GENETIC ALGORITHM

The modeling of the solar PV array and the regular energy output of the system is given below. And the designed model is of around 382 kW and 192V and the battery bank state of charging and the discharging are also mentioned and the States of discharge shout not beyond 100% which reduces the lifetime of the battery. The optimal sizing method describe can be applied to other design other type of hybrid system listed in table1. ASC and the COE are

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Performance assessment of domestic photovoltaic power plant with a storage system

Performance assessment of domestic photovoltaic power plant with a storage system

Abstract: Grid-connected low voltage photovoltaic power plants cover the majority of the power capacity installed in Italy. They offer an important contribution to the power demand of the utilities connected but, due to the nature of the solar resource, the night time consumption can be satisfied only withdrawing the energy by the national grid, at the price of the energy distributor. Thanks to the improvement of storage technologies and the decreasing of costs, the installation of a system of battery looks a promising solution. In this paper, a model-based approach to analyze and discuss the performance of a domestic photovoltaic power plant with a storage system is presented.

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Weissbart, Christoph
  

(2019):


	Numerical frameworks for challenges to the transformation of power markets: technology choice, cooperation, model capability.


Dissertation, LMU München: Volkswirtschaftliche Fakultät

Weissbart, Christoph (2019): Numerical frameworks for challenges to the transformation of power markets: technology choice, cooperation, model capability. Dissertation, LMU München: Volkswirtschaftliche Fakultät

Concerning the detail of modeling, an important issue addressed by Pfenninger et al. (2014) is the high penetration of electricity from intermittent RES, which results in the further need for energy system models with a high spatial and temporal resolution and an extended representation of flexibility options. Therefore, we describe the spatial prop- erties not only by the spatial coverage of the modeled region, but also through the spatial resolution, which represents the granularity of the model. Moreover, different models might represent technologies and their respective costs at varying levels of detail. We captured these differences with the criteria “included costs” and “included technologies”. In contrast to Hall and Buckley (2016), thermal generation technologies are mentioned explicitly, besides RES technologies and storage technologies. Since for many research questions a very detailed representation of those generation technologies is necessary, we further introduce the “details of thermal generation” and “details of storage modeling” as criteria. Examples for the former are partial efficiencies, cross-time-step restrictions or time-dependent availabilities, whereas the latter include the power capacity, the reservoir capacity, additional inflows, and storage losses. The necessity for analyzing single models with respect to these two criteria follows directly from the increasing market penetra-

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Framework for the Integration of Distributed Energy Storage Device with the Future Renewable Electric Energy Delivery and Management System

Framework for the Integration of Distributed Energy Storage Device with the Future Renewable Electric Energy Delivery and Management System

In order to demonstrate the interconnectivity of the DESD with a Home Energy Management System (HEMS), we connected them via the MQTT network. The HEMS could be serving various objective functions such as: one, to regulate a power cap for the amount of power drawn from the grid by using the DESD to meet any extra load demand or two, to use the DESD based on time of usage (TOU) utility rates so as to charge the DESD when the cost of electricity is low during the day and then later discharge it at peak demand times (when the cost of electricity is typically high). To perform these operations effectively, HEMS periodically needs an updated value of he residual energy inside the DESD and also a mechanism to dispatch power commands to the DESD in order to charge or discharge it at a particular power level. The HEMS’ core algorithm works on the Matlab platform on a PC and so we also had an MQTT Client running on the same PC. For the sake of simplicity, the HEMS and MQTT Client exchanged data via a shared file interface. At every time step, HEMS reads the residual energy in the DESD, run it’s algorithm to achieve optimal power flow in to the house from sources such as the grid and a simulated PV panel, and comes up with a dispatch power command for the DESD. The MQTT Client then forwards this command to the DESD and reads back an updated value of the residual energy capacity from the DESD. The HEMS reads this value of residual capacity in the next time step. Figure 4.8 shows the integration of DESD with the HEMS.

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Performance of a Battery Electric Vehicle with Self Charging Capacity for Its Own Propulsion

Performance of a Battery Electric Vehicle with Self Charging Capacity for Its Own Propulsion

The battery electric vehicle based on the required considerations is made ready with all connections and support on the chassis frame. The outcome of the vehicle was expected to supply the source continuously to charge the battery when the vehicle is moving forward. The connections made so far, provided the supply source based on the need and it is observed in many numbers of trials. A set of 4 Lead acid batteries with specifications as 12V and 7Ah is used in the work. The supply from these batteries is found to be useful in moving the vehicle for a distance of around 4 km. During the course the rotational energy is extracted by an alternator and transferred to a DC to DC converter where it is stepped up. This is finally supplied to battery source to recharge making it as a closed circuit.

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Capacity fade modelling of lithium ion battery under cyclic loading conditions

Capacity fade modelling of lithium ion battery under cyclic loading conditions

parameters affecting the battery life. It is found that multiple factors affect the performance and the battery life, most of which are interlinked. The SEI layer forms the irreversible coat- ing preventing the chemical reaction. This is captured by linking the model to the partial molar concentration. This is again linked with the operating temperature which is a function of the convective heat transfer coefficient. The model can be used as an optimisation tool

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Potassium Vanadate Nanobelt as a High-Capacity Cathode Material for Li-ion Battery

Potassium Vanadate Nanobelt as a High-Capacity Cathode Material for Li-ion Battery

hydrothermal method as cathode material for Li-ion battery. The nanobelts showed good lithium ion insertion and extraction ability. At a current density of 15 mA g -1 , it exhibited an initial discharge capacity of 268.9 mAh g -1 . After 20 cycles, the discharge capacity of 180 mAh g -1 was maintained. When the current density was increased to 75 mA g -1 , the nanobelts still exhibited a high discharge capacity of 197.5 mAh g -1 with the capacity retention of 70.8% after 25 cycles.

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Battery energy storage system modeling : a combined comprehensive approach

Battery energy storage system modeling : a combined comprehensive approach

clearly visible on Fig. 12(c) where it can be seen that all the cells are similar, i.e., same IC signature, but that their initial voltage is different and lower for cells with a lower SOC. Fig. 12(b) highlights the com- plicated relationship at the pack level. At high voltage, the capacity usage in each SC appears shifted depending on the initial SOC, which was expected based on Fig. 12(c). The most noticeable changes are at low voltage where the last peak appears hugely broaden for some cells. This can be explained by the fact that at his stage, the cells that started at a low SOC are already fully discharged (peak is completed); whereas, the cells that started at a high SOC still have some capacity (on the peak). At the pack level, most cells finished the peak and thus have their voltage dropping sharply. As a result, there was a big dV for a small dQ. Consequently, the peak at the SC level appeared to broaden. This new graphical visualization tool for IC or DV curves, that will be referred at IC SC/P to differentiate it from the standard IC

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Wind & Solar Power Systems pdf

Wind & Solar Power Systems pdf

India has 9 million square kilometers land area with a population over 900 million, of which 75 percent live in agrarian rural areas. The total power generating capacity has grown from 1,300 MW in 1950 to about 100,000 MW in 1998 at an annual growth rate of about nine percent. At this rate, India needs to add 10,000 MW capacity every year. The electricity network reaches over 500,000 villages and powers 11 million agricultural water-pumping stations. Coal is the primary source of energy. However, coal mines are concentrated in certain areas, and transporting coal to other parts of the country is not easy. One-third of the total electricity is used in the rural areas, where three-fourths of the population lives. The transmission and distribu- tion loss in the electrical network is relatively high at 25 percent. The envi- ronment in a heavily-populated area is more of a concern in India than in other countries. For these reasons, the distributed power system, such as wind plants near the load centers, are of great interest to the state-owned electricity boards. The country has adopted aggressive plans for developing these renewables. As a result, India today has the largest growth rate of the wind capacity and is one of the largest producers of wind energy in the world. 5 In 1995, it had 565 MW of wind capacity, and some 1,800 MW

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Battery Equalization Control Strategy Based on Fuzzy Control

Battery Equalization Control Strategy Based on Fuzzy Control

U = {S M B} (6) The output variable I eq is related to the two input variables  U and U . The equalization current determines the equalization time of the battery directly. The balancing current is small, the equalization time is long, the balancing current is large, and the equalization time is short. However, if the equalization current is set too small, it will greatly extend the balance time and reduce the efficiency. If the balanced current is too large, it may lead to the excessive increase of the battery temperature and lead to the heat imbalance. Therefore, it is very necessary to accurately design the balance current of the battery. This paper fully considers the actual value range of the battery and design the domain to be [0,5], and the basic domain and the corresponding fuzzy set are as follows.

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