Ultracapacitor Research Articles

Mitigation of sulfation in lead acid battery towards life time extension using ultra capacitor in hybrid electric vehicle

Batteries act as one of the primary sources of energy for high power Hybrid Electric Vehicle (HEV). The life of the battery becomes a significant constraint while building an HEV. So researchers found Lithium-ion batteries are more suitable for HEV with a better lifecycle. But the manufacturing cost of Lithium-ion batteries is expensive. Thus, while designing an economic HEV, the cost of batteries also a constraint. In subsequent years, lead-acid batteries are found one of the best alternatives for lithium-ion. Sulfation is the main problem in lead-acid batteries. So de-sulfation is a solution to recover the sulphated lead-acid battery. But de-sulfation was not found as a better solution for preventing sulfation. Hence battery management system for proper charging or discharge is found as a passive solution for the sulfation. In literature, many methods are reviewed related to proper charging and a discharging controller which may trap in sulfation problem. Hence, this paper, an Atom Search Algorithm (ASA) based Hybrid Energy Storage System (HESS) is designed to enable proper charging and discharging controller for increasing the lifecycles of the lead-acid battery by avoiding sulfation. The lead-acid battery is connected with Ultra-Capacitor (UC) through a bidirectional DC-DC converter to enable proper charging and to discharge of controller in a. The lifetime extension of lead-acid battery is attained by maintaining the proper charging and discharging through the conservation of Depth of Charge (DOC) and State of Charge (SOC). The charging and discharging controller of the lead-acid battery are enabled by a rule-based control strategy in the converter. The optimal operation of the converter is to provide essential supply to meet the load drive cycle as well as battery charging progress. To avoid battery's dry conditions, UC is playing the leading role to supply by the converter. The controller action is performed through the consumption of the Fractional-Order Proportional Integral Derivative Controller (FOPID) in the bidirectional DC-DC converter. The optimal switching operations are selected with the utilisation of the ASA algorithm. The proposed method is implemented in MATLAB/ Simulink and contrasted with existing methods. Finally, the proposed method extends the lifecycles of the battery to 7500 cycles by proper charging and discharging controller.

Modeling and Optimal Tuning of Hybrid ESS Supporting Fast Active Power Regulation of Fully Decoupled Wind Power Generators

The frequency stability of the power system is challenged by the high penetration of power electronic interfaced renewable energy sources (RES). This paper investigates the improvements of the frequency response of fully decoupled wind power generators (FDWG) by proposing a novel generic model implementation of ultracapacitors (UC) within a hybrid scheme in real-time simulations of wind power plants. UCs are selected as ideal power sources in fast active power-frequency control due to their high power density and fast-reacting speed. Batteries and UCs combined hybrid energy storage systems (HESS) are formed to complement their characteristics. Droop-based and frequency derivative-based control and virtual synchronous power (VSP) are the selected control strategies to support power system frequency stability. The best trade-off between frequency performance and HESS cost is found by solving a proposed optimization problem formulation. The proposed optimization problem is used to define the HESS size and the controller parameters. The optimization results show how the fast active power-frequency response is enhanced by the fast UC power injection. It also shown that VSP leads to faster frequency support than the droop-based control and the frequency derivative control.

TokenSmart: Distributed, Scalable Power Management in the Many-Core Era

Centralized power management control systems are hitting a scalability limit. In particular, enforcing a power cap in a many-core system in a performance-friendly manner is quite challenging. Today’s on-chip controller reduces the clock speed of compute domains in response to local or global power limit alerts. However, this is transparent to the operating system (OS), which continues to request higher clock frequency based on the workload characteristics acting against the centralized on chip controller. To address these issues, we introduce TokenSmart, which implements a scalable distributed frequency control heuristics within the OS, using a novel token-based mechanism. The compute units are connected in a ring-topology allowing minimal meta-data to be passed along with the token value for regulating power budget. We explore different heuristics to assign tokens smartly across the units. This results in efficient power regulation and sustenance of turbo frequencies over a longer duration. The methodology is implemented within the Linux kernel of a real IBM POWER9 many-core system. The experimental results show a considerable boost of about 4 percent in throughput of PostgreSQL benchmark with a tangible 18 percent decrease in power consumption.

Assessing the performance of vehicles powered by battery, fuel cell and ultra-capacitor: Application to light-duty vehicles and buses

As alternative vehicle technologies gain more importance in the market, this work assesses the possibility of a multi power source vehicle configuration by evaluating the performance of an electric vehicle powered by battery (BEV), fuel cell (FCEV), ultra-capacitor (UC) and combination of the former. A flexible vehicle simulation model was developed in MATLAB-Simulink and vehicle performance was evaluated in various 1 Hz certified cycles, enabling the assessment of light duty and heavy-duty vehicles powered by various power sources. The developed model accurately estimates energy consumption and range of passenger vehicle with an average absolute error of less than 4% and 2% for the electric bus. The study showed that BEV has the least energy consumption (23%), followed by FCEV (65%) compared to internal combustion engine (ICE) vehicles in real world conditions. Regarding the combination of energy sources, an increase in range by 10% is estimated when battery is combined with fuel cell, while combining ultra-capacitor with battery enables a lifetime extension of battery life by 10%, with negligible change in range. Combining secondary sources with fuel cell shows a reduction of total fuel cell capacity by 40% for the same operation. Analysis on ultra-capacitor showed negative response with light duty vehicle, while for buses the usage of batteries shows positive results with negative impacts on cost and recharging time. Ultra-capacitors are highly recommended for short-frequent trips with fast recharging and a life of 20 years, while fuel cells as a primary energy source are recommended for the long-range trips in coaches and trucks.

Evaluating the Performance of Hybrid Ultra Capacitor (HUC) in a 1.5kw Solar Powered Microgrid with Hybrid Energy Storage System (HESS)

Evaluating the Performance of Hybrid Ultra Capacitor (HUC) in a 1.5kw Solar Powered Microgrid with Hybrid Energy Storage System (HESS)

A Preliminary Techno-Economic Comparison between DC Electrification and Trains with On-Board Energy Storage Systems

The paper presents a preliminary technical-economic comparison between a 3 kV DC railway and the use of trains with on-board storage systems. Numerical simulations have been carried out on a real railway line, which presents an electrified section at 3 kV DC and a non-electrified section, currently covered by diesel-powered trains. Different types of ESS have been analyzed, implementing the models in Matlab/Simulink environment. A preparatory economic investigation has been carried out.

The Impact of CPU Voltage Margins on Power-Constrained Execution

CPUs typically operate at a voltage which is higher than what is strictly required, using voltage margins to account for process variability and anticipate any combination of adverse operating conditions. However, these worst-case scenarios occur rarely, if ever, thus the operating voltage is overly pessimistic resulting in excessive power dissipation which leads to decreased performance under power capping. In this paper, we investigate the impact of reducing voltage margins beyond the nominal level on the efficiency of CPU power capping mechanisms, for three commercial systems, two Applied Micro ARMv8 micro-servers (X-Gene2 and X-Gene3) and an Intel x86-64 (Xeon E3). We show that CPU power capping at reduced voltage margins compared with Intel’s RAPL and Dynamic Frequency Scaling (DFS) mechanisms results in performance improvement by up to 64 and 24 percent on average, respectively. In combination with state-of-the-art thread packing, the reduction of CPU voltage margins results in 36, 33 and 27 percent performance improvement compared with RAPL and DFS for the Xeon E3 and the X-Gene processors, respectively. Also, we validate the robustness of our approach with a set of long-running experiments and show that significant energy gains can be achieved even when considering the cost of checkpointing and recovery in large-scale systems.

Investigation on intelligent controllers performace used in electric vehicle application

ABSTRACT The main objective of this work is to design a control strategy of a hybrid energy storage system (HESS) to switch the battery and ultracapacitor (UC) as per EV requirement. To achieve the objective, a math function based (MFB) controller has been designed by considering four math functions further those can individually be programmed according to the speed of the motor. The speed of an electric motor plays a vital during the changing of energy sources present in HESS, and the main function of designed MFB controller to regulate the pulse signals which is given to the switches present in the unidirectional converter (UDC) as well as a bidirectional converter (BDC). In this work, three different controllers’ proportional–integral controller (PI), proportional integral derivative (PID) controller, and fuzzy logic controller (FLC) are used individually for generating required pulse signals to the switches present in DC-DC converters. Finally, the proposed objective can be achieved by combining MFB individually with PI or PID or FLC made a separate hybrid controller. Comparative analysis has been made among three hybrid controllers based on different factors. The entire circuit can be implemented with three hybrid controllers separately in MATLAB/Simulink with four modes corresponding to the motor’s speed.

Resource Management for Power-Constrained HEVC Transcoding Using Reinforcement Learning

The advent of online video streaming applications and services along with the users’ demand for high-quality contents require High Efficiency Video Coding (HEVC), which provides higher video quality and more compression at the cost of increased complexity. On one hand, HEVC exposes a set of dynamically tunable parameters to provide trade-offs among Quality-of-Service (QoS), performance, and power consumption of multi-core servers on the video providers’ data center. On the other hand, resource management of modern multi-core servers is in charge of adapting system-level parameters, such as operating frequency and multithreading, to deal with concurrent applications and their requirements. Therefore, efficient multi-user HEVC streaming necessitates joint adaptation of application- and system-level parameters. Nonetheless, dealing with such a large and dynamic design space is challenging and difficult to address through conventional resource management strategies. Thus, in this work, we develop a multi-agent Reinforcement Learning framework to jointly adjust application- and system-level parameters at runtime to satisfy the QoS of multi-user HEVC streaming in power-constrained servers. In particular, the design space, composed of all design parameters, is split into smaller independent sub-spaces. Each design sub-space is assigned to a particular agent so that it can explore it faster, yet accurately. The benefits of our approach are revealed in terms of adaptability and quality (with up to to $4\times$ 4 × improvements in terms of QoS when compared to a static resource management scheme), and learning time ( $6 \times$ 6 × faster than an equivalent mono-agent implementation). Finally, we show that the power-capping techniques formulated outperform the hardware-based power capping with respect to quality.

Optimal Sizing of On-Board Energy Storage Systems and Stationary Charging Infrastructures for a Catenary-Free Tram

This paper introduces an optimal sizing method for a catenary-free tram, in which both on-board energy storage systems and charging infrastructures are considered. To quantitatively analyze the trade-off between available charging time and economic operation, a daily cost function containing a whole life-time cost of energy storage and an expense of energy supplies is formulated for the optimal sizing problem. A mixed particle swarm optimization algorithm is utilized to find optimal solutions for three schemes: (1) ultracapacitors storage systems with fast-charging at each station; (2) battery storage systems with slow-charging at starting and final stations; (3) battery storage systems with fast-swapping at swapping station. A case study on an existing catenary-free tramline in China is applied to verify the effectiveness of the proposed method. Results show that a daily-cost reduction over 30% and a weight reduction over 40% can be achieved by scheme 2, and a cost saving of 34.23% and a weight reduction of 32.46% can be obtained by scheme 3.

Optimized configuration and economic evaluation of on-board energy storage system for subway vehicles

The on-board supercapacitor energy storage system for subway vehicles is used to absorb vehicles braking energy. Because operating voltage, maximum braking current and discharge depth of supercapacitor have a great influence on its rational configuration, there are theoretical optimum values based on the analysis of vehicle regenerative braking theory, whose mathematical models for the supercapacitor bank power and capacity requirements are established. To meet braking energy recovery, constrained configuration method is based on the power, capacity and discharge depth of the supercapacitor bank. The supercapacitor bank optimization process is given, and then the effect of operating voltage and temperature on the life of supercapacitor is analyzed from the view of economy. Calculation models of initial investment, operation–maintenance cost and economic benefit of the system are given. The simulation results show that the supercapacitor bank based on power, capacity and discharge depth can meet the requirement of braking energy recovery for subway vehicles. Meanwhile, the economic evaluation of the project shows that the project will achieve good social and economic benefits.

Performance Analysis of Power Sharing Control Strategies for Battery/Ultracapacitor Hybrid Energy Storage Based Electric Vehicle

Electric Vehicles (EVs) gaining demand worldwide, still face the challenge of adapting the Energy Storage System (ESS) with high power and energy density. Such an ESS is essential for providing desirable dynamic performance and driving range. The power demand from the ESS varies frequently in a wide range in an urban drive due to frequent stops and starts of the vehicle. This paper proposes an ESS with a hybrid combination of battery and ultracapacitor (UC) along with two power sharing control strategies which assures the desirable EV performance in an urban drive cycle. This proposed hybrid ESS (HESS) also leads to the improvement in the battery cycle life, dynamic response as well as energy efficiency of the EV. This work encompasses the details of the proposed control strategies viz. ‘Speed Related Control’ (SRC) and ‘Fuzzy Based Control’ (FBC). The simulation results show that the performance of FBC is better in limiting and leveling the battery current and hence improving the battery cycle life. The paper also includes the hardware results based on a laboratory prototype of the proposed EV system validating the performance of the proposed control strategies.

Gap‐Plasmon Coupled Nanopillar Array to Promote Upconversion Luminescence

This work theoretically explored the well-defined nanogap arranged as an upconversion (UC)/gold capping layer photonic nanopillar array on a back-reflecting film-coated Si substrate. The gap-plasmon (GP)-coupled periodic nanopillar array with encapsulating the upconversion layer (denoted as GPNA) is suggested to promote the upconversion luminescence (UCL) intensity at excitation and emission wavelengths. The optical localized-plasmon properties of the GPNA platform were probed by finite-difference time-domain (FDTD) method. With tweaking the geometric design parameters such as a cap thickness and gap distance, the GPNA platform can induce a prominent GP mode between the UC cap layer, thus leading to the significant plasmon-driven optical electromagnetic field amplification within the UC layer followed by substantial light absorption and UCL promotion. This proposed GP-coupled nanopillar array would pave the alternative way for a broad range of plasmon-sensitized applications which are able to absorb the incident excitation and resultant emission light.

Performance Assessment of an Islanded Hybrid Power System with Different Storage Combinations Using an FPA-Tuned Two-Degree-of-Freedom (2DOF) Controller

During the past few decades, there has been significant growth in the renewable energy market because of increased concern over global warming and the continuous depletion of fossil fuel resources. There is a promising solar thermal technology that utilizes low-temperature heat to generate electricity. The conversion process of thermal energy to electricity is based on the principle of an organic Rankine cycle (ORC). This study investigated a novel islanded hybrid power system consisting of an ORC low temperature solar thermal system, wind (WTG), diesel generation (DEG) set, and combined application of an energy storage system (ESS), such as a battery (BESS), super magnetic energy storage (SMES), and an ultracapacitor (UC) unit. Furthermore, the hybrid system was employed with a single controller (one of proportional-integral (PI), PI with derivative (PID), two-degree-of-freedom (2DOF) PI, and 2DOF PID controllers) with proportionate gains to the DEG, and the ESS, which is another unique aspect of this work. Moreover, a comparative performance assessment of the flower pollination algorithm (FPA) to tune the PI, PID, 2DOF PI, and 2DOF PID controllers was carried out. Finally, the performance of the above hybrid system was compared with different ESS combinations, namely, (i) only BESS, (ii) BESS + UC, and (iii) BESS + SMES. The simulation results indicated that a renewable integrated isolated power system with BESS + SMES provided a better response than the other ESS combinations. In fact, the presence of comparative dynamic responses verified the superiority of an FPA-tuned 2DOF PID compared with other FPA-tuned controllers.

Lyapunov based adaptive controller for power converters used in hybrid energy storage systems

Depleting fossil fuels, natural gas resources, escalating oil prices, and global warming issues have made fuel cell (FC) based electric vehicles (EVs), a vital replacement to its conventional counterpart. Modeling of such a system contains power-conditioning circuitry, which exhibits nonlinear nature. In this paper, a model for hybrid electric vehicle is proposed with FC as primary source, whereas ultra-capacitor (UC) and battery are secondary sources. All the sources are linked with a direct current (DC) bus comprising of DC-DC converters. The study of the system is done mathematically and simulations are performed on MATLAB/Simulink. The dynamic model based on Lyapunov based adaptive control technique with model uncertainties designed to accomplish the following objectives. Firstly, the perfect regulation of DC bus voltage having minimum steady-state error under the load variations. Secondly, current of battery and UC precisely followed quickly under their relating reference values. Finally, asymptotically stability of the closed loop system. Proposed controller performances are analyzed using MATLAB/Simulink and comparative analysis is done with the sliding mode controller (SMC) and proportional integral derivative (PID) controller, which demonstrates the closed-loop stability of the proposed controller. Moreover, all control objectives are achieved efficiently.

Biogenic-Mediated Synthesis of the Cs2O-MgO/MPC Nanocomposite for Biodiesel Production from Olive Oil.

In this work, a biogenic-mediated approach is successfully used to synthesize a novel heterogeneous Cs2O–MgO/MPC basic nanocomposite. For the first time, the established technicality employs pomegranate seed extract that gives a green capping fuel and reducing mediators during an aqueous solution combustion process of metal ion precursors. The synthesized nanocomposites were identified by X-ray diffraction, Fourier transform infrared, N2 isotherms, field emission scanning electron microscopy, and CO2-TPD analyses. The transesterification process of olive oil was used to evaluate the catalytic performance. The nanocomposite displayed outstanding catalytic efficiency stemming from the boosting of the reactant and product diffusion. The transesterification activity and the optimization design were assessed by applying the response surface methodology. Based on the experimental tests, the finest experimental conditions with a biodiesel yield of 96.1% are 4 h, 4% catalyst amount, an oil/methanol ratio of 1:15, and a temperature of 65 °C. The predicted optimal conditions based on the statistical model are 6 h contact time, 5.2 % catalyst dose, 65 °C reaction temperature, and 1:15 oil/methanol molar ratio, attaining a biodiesel yield of 95.18%. The catalyst reusability has been performed almost continuously up to four cycles, with no loss of the active constituents. The obtained biodiesel demonstrated characteristics close to those of international standards of biodiesel. Besides, the process employed in this study demonstrated significant potential for further development and commercialization and is cheaper than the refined vegetable oil used in traditional approaches of biodiesel manufacturing.

Dual dielectric cap gold nanoslits array optical resonance filter with large figure-of-merit.

In this work, we investigate a gold nanoslits array optical transmission filter with dual dielectric cap layers on top of the metal nanoslits. By integrating a low index of refraction dielectric layer between a high index of refraction dielectric cap layer and the gold nanoslits, a narrow spectral linewidth optical filter with a transmission peak far away from the Rayleigh anomaly wavelength is shown. Furthermore, we propose a figure-of-merit as the ratio of the spectral distance between a transmission peak and the Rayleigh anomaly over the spectral linewidth to characterize the performance of gold nanoslits optical filters. It is shown that dual dielectric cap gold nanoslits array optical filters have significantly larger figure-of-merits than that of traditional single dielectric cap gold nanoslits array optical filters.

Hydrone: Reconfigurable Energy Storage for UAV Applications

Unmanned aerial vehicles (UAVs) are often used in mission-critical applications, requiring a critical criterion in flight time. Unfortunately, severe power fluctuations, caused by specific flight patterns, degrade the deliverable capacity of the battery and hamper the flight time. A common approach to mitigating power fluctuations is to employ a hybrid energy storage system using a Li-ion battery with an ultracapacitor (UC). However, the conventional scheme poses inherent problems of low-energy density and power leakage due to the use of the UC and the supplementary hardware required for hybrid storage. In this article, we propose Hydrone, a reconfigurable battery architecture that maximizes the flight time of UAVs, overcoming the previous limitations. Hydrone addresses two key challenges that arise when hybrid energy storage is utilized in UAVs: 1) capacity loss and 2) power leakage. First, the proposed scheme compromises the capacity loss of hybrid storage by using a minimal capacity UC for use as a buffer to counteract the power fluctuations. Second, the power leakage of the hybrid battery is minimized by draining power from the UC only when it is necessary. To this end, the Hydrone architecture provides reconfigurability in hardware and offers two modes of battery operation, i.e., a battery-only mode and a hybrid mode. An appropriate operation is then selected at runtime depending on the flight situation and battery status. To switch modes, we employed a reinforcement learning-based switch control, reflecting the power fluctuation adequately on the flight and battery states. We implemented a hardware prototype to demonstrate the efficiency of Hydrone. Our extensive evaluation shows that the flight time of a UAV is prolonged up to 39% in our experiment setup.

Modeling Onboard Energy Storage Systems for Hybrid Traction Drives

The development of hybrid technologies for traction rolling stock manufactured for mainline, urban, and industrial railroad transport is a trend capable of improving the energy efficiency of transportation much better than any new conventional projects. The integrated and detailed study of the joint operation of main energy sources (catenary system, diesel generator outfits) and onboard energy storage systems as part of a single energy network on advanced-type traction rolling stock is of major importance to the broad and successful adoption of hybrid locomotives with a combined power plant. The highest efficiency in accumulating and utilizing electrical braking energy is attained in energy storage systems based on electrochemical current sources (electric batteries) and high-capacity supercapacitor batteries. This article considers the issue of mathematically modeling these onboard energy storage systems and the features of controlling a hybrid traction electric drive on rolling stock.

Improvement of Blood Glucose, Serum Antioxidant Status and Liver Enzyme Changes by Hydroalcoholic Extract of Solanum melongena Green Cap in Diabetic Rats

Background and objectives: Diabetes is associated with a wide range of disorders including oxidative stress. Solanum melongena L. possessesantioxidant compounds and was introduced as an antidiabetic herb in Asian traditional texts. The aim of the present study was to investigate the effect of hydroalcoholic extract of S. melongena green cap on blood glucose and antioxidant status of liver in diabetic rats. Methods: In this experimental study, the extract was prepared by maceration method and 42 male Wistar rats (190-220 g) were divided into 6 groups (n=7/groups) including: 1. Control; 2. diabetic groups receiving 1 mL distilled water daily; groups 3 and 4 of normal rats receiving 100 and 200 mg/kg extracts, respectively, and diabetic treated groups 5 and 6 with 100 and 200 mg/kg extract, respectively. Diabetes was induced by intraperitoneal injection of streptozotocin (55 mg/kg). At the end of study, serum levels of fasting blood glucose (FBG), aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), total protein, nitric oxide (NO) level and total antioxidant capacity (FRAP) were measured. Histological changes of liver were also assessed using hematoxylin and eosin staining. Results:Treatment of diabetic animals with the extract of S. melongena cap (100 and 200 mg/kg) significantly reduced serum levels of FBG, ALT, ALP, NO (p <0.001) and AST (p=0.017), while total protein (p <0.001) and FRAP (p=0.007) levels increased significantly. The extract also improved the liver tissue changes induced by diabetes. Conclusion:Solanum melongena cap is effective in improving liver complications and serum antioxidant status in diabetic rats.