Accurate Parameters Identification of a Supercapacitor Three-Branch Model

Supercapacitors are becoming increasingly important storage system components. To effectively control their terminal voltage, even in real time, numerous circuit models capable of faithfully simulating their behavior in energy systems and various applications are being explored. The three-branch supercapacitor model appears to be a good compromise between simplicity and accuracy. Typically, this model lacks accuracy in dynamic cycling and long stand-by periods. In this study, a new model identification method based on the state equations of the circuit is described and tested on a 400 F supercapacitor, and the obtained results are validated by measurements. Such an approach, suitably optimized, provides good agreement with the measurements, with discrepancies below 50 mV even in repeated cycles. In the static identification, after 90 minutes of self-discharge, the discrepancy was approximately 5 mV. The study also discusses the sensitivity of the model output to the circuit parameters, which is useful for choosing the appropriate timespan for parameter optimization and introduces variable leakage resistance and a method for its determination. Through this parameter, good agreement with the measurements is observed during the long self-discharging phases. A discrepancy of less than 50 mV between the measured and computed results is observed after one week. The union of the circuit state equations based model and the nonlinear leakage resistance determination allows the three-branch circuit model to achieve a high accuracy both in real-time simulation and in the presence of long stand-by phases

Online Parameter Estimation for Supercapacitor State-of-Energy and State-of-Health Determination in Vehicular Applications

WOS:000536291000079Online accurate estimation of supercapacitor state-of-health (SoH) and state-of-energy (SoE) is essential to achieve efficient energy management and real-time condition monitoring in electric vehicle (EV) applications. In this article, for the first time, unscented Kalman filter (UKF) is used for online parameter and state estimation of the supercapacitor. In the proposed method, a nonlinear state-space model of the supercapacitor is developed, which takes the capacitance variation and self-discharge effects into account. The observability of the considered model is analytically confirmed using a graphical approach. The SoH and SoE are then estimated based on the supercapacitor online identified model with the designed UKF. The proposed method provides better estimation accuracy over Kalman filter (KF) and extended KF algorithms since the linearization errors during the filtering process are avoided. The effectiveness of the proposed approach is demonstrated through several experiments on a laboratory testbed. An overall estimation error below 0.5% is achieved with the proposed method. In addition, hardware-in-the-loop experiments are conducted and real-time feasibility of the proposed method is guaranteed

Supercapacitor Electro-Mathematical And Machine Learning Modelling For Low Power Applications

Low power electronic systems, whenever feasible, use supercapacitors to store energy instead of batteries due to their fast charging capability, low maintenance and low environmental footprint. To decide if supercapacitors are feasible requires characterising their behaviour and performance for the load profiles and conditions of the target. Traditional supercapacitor models are electromechanical, require complex equations and knowledge of the physics and chemical processes involved. Models based on equivalent circuits and mathematical equations are less complex and could provide enough accuracy. The present work uses the latter techniques to characterize supercapacitors. The data required to parametrize the mathematical model is obtained through tests that provide the capacitors charge and discharge profiles under different conditions. The parameters identified are life cycle, voltage, time, temperature, moisture, Equivalent Series Resistance (ESR) and leakage resistance. The accuracy of this electro-mathematical model is improved with a remodelling based on artificial neuronal networks. The experimental data and the results obtained with both models are compared to verify and weigh their accuracy. Results show that the models presented determine the behaviour of supercapacitors with similar accuracy and less complexity than electromechanical ones, thus, helping scaling low power systems for given conditions

Development of a Power Factor Corrected High Current Supercapacitor Charger for a Surge Resistant UPS

The Uninterrupted Power Supplies (UPSs) provide short term power back up to electrical loads when the mains power fail. Usually UPSs employ battery packs as the energy storage device. However the limitations of battery packs can affect the UPS performance. As an alternative energy storage device, the supercapacitor (SC) technology is well developed over the past 30 years. Due to recent developments, single cell commercial supercapacitors are available up to about 5000 farads. Over the past 10 years, supercapacitor direct current (DC) voltage ratings have gradually increased to about 2.7 V/cell. New lithium based supercapacitor families have DC ratings up to 3.5 V/cell. For the high current applications, the supercapacitors have some advantages over batteries, which are the low effective series resistance (ESR), high power densities and high surge withstand capability. This thesis is a continuation of the work begun by Kozhiparambil, P. K. on Surge Resistant Uninterrupted Power Supply (SRUPS). The reason for this continual research is due to identify weaknesses in original of SRUPS work with regard to the design of the charger. To reduce the components contain, also achieve common mode transient rejection capability, a flayback mode high current charger with power factor correction has been developed for charging the SC banks. The prototype circuit includes multiple SC banks to transfer the energy from the 240 V, 50 Hz power line to the load maintaining high isolation level. The loads receive continuous and surge free power from the SC banks, and has electrical isolation from the main power line. An IGBT is used as a switch for the flyback charger, which has the advantage of high current capability. The experimental results show the design was valid for the SRUPS and it demonstrated the capability to transfer the energy through a flyback charger with power factor correction

Advances in Supercapacitor Technology and Applications

Energy storage is a key topic for research, industry, and business, which is gaining increasing interest. Any available energy-storage technology (batteries, fuel cells, flywheels, and so on) can cover a limited part of the power-energy plane and is characterized by some inherent drawback. Supercapacitors (also known as ultracapacitors, electrochemical capacitors, pseudocapacitors, or double-layer capacitors) feature exceptional capacitance values, creating new scenarios and opportunities in both research and industrial applications, partly because the related market is relatively recent. In practice, supercapacitors can offer a trade-off between the high specific energy of batteries and the high specific power of traditional capacitors. Developments in supercapacitor technology and supporting electronics, combined with reductions in costs, may revolutionize everything from large power systems to consumer electronics. The potential benefits of supercapacitors move from the progresses in the technological processes but can be effective by the availability of the proper tools for testing, modeling, diagnosis, sizing, management and technical-economic analyses. This book collects some of the latest developments in the field of supercapacitors, ranging from new materials to practical applications, such as energy storage, uninterruptible power supplies, smart grids, electrical vehicles, advanced transportation and renewable sources

Hybrid heterogeneous energy supply networks

Abstract—Efficient energy supply, storage, and distribution are key technical challenges for design and operation of electronic systems. In particular, energy supply is the most scarce resource and constraint for mobile embedded systems where the supply lifetime, cost, weight, size, and portability are major concerns. With the advent of newer electrical energy supply and storage technologies, energy supplies with differing energy/power storage densities, cost, size, and recycling abilities are becoming available. Efficient system design requires an exact matching between the fluctuating load demands and the underlying energy resources. Combining the energy supplies in a hierarchical way creates a unique opportunity for efficient matching and variable load serving. Such a heterogeneous hybrid network of energy supply components could address a variety of power needs and serve a much broader range of system loads with a high efficiency. This paper presents a Hierarchial Architecture of Heterogenous Electrical Energy Supplies (HierArcHEES) that can be tuned to different load demands. I

Various analytical models for supercapacitors: a mathematical study

Supercapacitors (SCs) are used extensively in high-power potential energy applications like renewable energy systems, electric vehicles, power electronics, and many other industrial applications. This is due to SCs containing high-power density and the ability to respond spontaneously with fast charging and discharging demands. Advancements in material and fabrication techniques have induced a scope for research to improve the application of SCs. Many researchers have studied various SC properties and their effects on energy storage and management performance. In this paper, various fractional calculus-based SC models are summarized, with emphasis on analytical studies from derived classical SC models. Study prevails such parameterized resistor- capacitor networks have simplified the representation of electrical behavior of SCs to deal with the complicated internal structure. Fractional calculus has been used to develop SC models with the aim of understanding their complicated structure. Finally, the properties of different SC models utilized by various researchers to understand the behavior of SCs are listed using an equivalent circuit

Printed Supercapacitors for Energy Storage and Functional Applications, Modeling, Analysis, and Integration

Supercapacitors (SCs), also known as ultracapacitors or electrochemical double-layer capacitors (EDLCs), have emerged as a remarkable class of energy storage devices that bridge the gap between conventional capacitors and batteries. These devices exhibit exceptional power density and long lifecycle, making them well-suited for a wide range of applications, from powering portable electronics to enabling rapid energy storage and release in various industrial systems. Unlike batteries, SCs store energy through the physical separation of charges at the electrode-electrolyte interface, leading to rapid charging and discharging capabilities. However, SCs are not without their challenges, notably leakage current and self-discharge, which can impact their long-term performance and practical utility. As the demand for energy-efficient and responsive power solutions intensifies, a thorough understanding of SCs’ behavior, coupled with accurate modeling techniques, becomes imperative. This thesis delves into this intricate realm, offering insights, models, and practical applications that collectively contribute to harnessing the potential of SCs across diverse domains. In the realm of energy storage and power management, this thesis presents a cohesive exploration of SCs’ behavior and its practical implications through a series of five interrelated research papers. Focusing on the context of charging and discharging within series-connected SC modules under varying load conditions, the research advances an innovative exponential model that elegantly captures complex behaviors with less than 4% simulation error over extended time frames (31 days). The initial study introduces an improved exponential equivalent circuit model (ECM) that elegantly characterizes the charging and discharging dynamics of series-connected SC modules. Leveraging a single-variable leakage resistance (VLR) approach, the model adeptly accounts for diverse self-discharge mechanisms. Unlike existing literature ECMs, this ECM’s simplicity and accuracy render it suitable for real-world applications in both short and long terms. The investigation extends to the modeling of multiple SC energy storage modules, providing insights into the behavior of SCs within varying configurations. Expanding into the domain of Internet of Things (IoT) applications, the research highlights the significance of energy storage devices for wireless sensor nodes. Acknowledging the limitations of traditional batteries, the study advocates for SCs as a viable solution. A refined exponential model is then proposed as a novel approach to predict the discharge behavior of disposable printed flexible SCs, ensuring concordance with experimental findings. This approach involves employing an innovative method to model the non-linearity of self-discharge in printed SCs, effectively capturing this phenomenon. This ECM’s adaptability and alignment with measured self-discharge results offer a promising avenue for optimal IoT device performance. Confronting the challenges of leakage current and self-discharge in SCs, the thesis presents a comprehensive framework. By proposing practical exponential ECMs, the study encapsulates nonlinear leakage and self-discharge phenomena. The empirical basis of these ECMs allows accurate prediction of discharge behaviors over extended periods, thereby holding potential for widespread practical application. A linear correlation was identified among the variables governing the exponential function of the equivalent parallel resistance (EPR) within the SC’s ECMs and the capacitance. The precision of the proposed ECMs was substantiated over an extended duration of 31 days, employing a diverse array of four distinct methodologies. The thesis also takes a statistical turn by conducting a meticulous analysis of experimental parameters across printed SCs. Employing established ECMs, the research unveils statistical distributions and correlations, empowering safer operation, and more informed decision-making. Monte Carlo simulation technique unveils the long-term performance of SCs, offering insights into consistency and aiding in risk assessment. The conducted statistical analysis has revealed a normal distribution pattern for all the parameters characterizing the printed SCs. Additionally, this thesis presents a methodology to ascertain the upper limit of potential standard deviation (std) in capacitance values across SCs within a module, aiming to ensure the seamless operation of the module without encountering malfunctions. Furthermore, an observed linear correlation has been established between the maximum potential std of capacitance values among SCs and the cumulative voltage stored within the module. Finally, the exploration expands to the activation of irreversible visual indicators (IVIs) through printed SCs, highlighting the potential of diverse monomer systems. The interplay of activation potential, coloration efficiency, and initial voltage underscores the feasibility of fully activating IVIs through series-connected SCs. In summary, this thesis intricately weaves together five research papers to construct a comprehensive narrative about the behavior, modeling, and application of SCs. From exponential models to statistical analyses and practical implementations, this work contributes to the broader understanding of SC dynamics and their potential within contemporary energy storage systems and IoT applications. The results-driven approach solidifies SCs' impact as a versatile energy storage device, emphasizing realworld performance, and evidence-based decisions