Supercapacitor Pack Research Articles

Distributed estimation of state-of-charge of supercapacitor packs: A consensus-based approach

It is crucial to estimate the state-of-charge (SoC) of a supercapacitor pack as cells are typically connected to form packs in practical applications. However, most of the existing studies adopted a centralized approach, which is to estimate all the single cells, and then calculate the overall SoC. When the total number of the cells comes to a high level, the burden of communication and the price of a single fault rise rapidly. To address this challenge, in this article, we propose a decentralized method for estimation of pack SoC, which is free of the central observer. We use the state space equation to model the supercapacitors in the physical modeling. In the cyber modeling, we construct their communication topology and apply a definition of pack SoC. A two-layer structure is proposed in which we design a Luenberger observer for each cell to estimate SoC of each cell. We propose a consensus-based algorithm to estimate its pack SoC. A laboratory testbed has been built to verify the effectiveness of the proposed method. Experimental results show that the proposed method can effectively implement the estimation and is more robust to communication failure than the centralized method.

Modeling and control of a new multi-port converter for hybrid energy system integration

This research introduces a new topology called the quasi-Z-source integrated isolated multiport bidirectional resonant DC-DC converter. The aim is to achieve cost-effective and efficient multi-directional power flow between photovoltaic (PV), battery/supercapacitor, and DC loads. The proposed topology ensures uninterrupted power supply to the loads and supports reverse power transfer through its bidirectional power flow capability. By combining quasi z-source and H-bridge resonant converters with an existing switch, a four-port converter is achieved without the need for separate converters or additional switches. The high-gain quasi z-source converter reduces the required voltage ratings of the battery and supercapacitor packs while enabling the utilization of a high-frequency transformer (HFT) with a low turns ratio. Isolation between the ports is achieved using a secondary center-tapped HFT equipped with a controlled full-wave rectifier on the secondary side, allowing bidirectional power flow. A power flow management system and corresponding control scheme are proposed to optimize the system's performance. The proposed system's performance is evaluated under various operating conditions, demonstrating its effectiveness in power flow management and overall efficiency. The results confirm the feasibility and effectiveness of the proposed system.

State of charge estimator based on tractable extended state observers for supercapacitor packs

A state of charge estimator (SOCE) is proposed for a single and a supercapacitor pack aimed at easy implementation and low computational cost extended state observers. This SOCE reduces modeling errors by implementing extended states using the classic supercapacitor equation. The proposed method involves a simple characterization of supercapacitors, which are tested using different discharge currents up to 40 [A] and subjected to added measurement noise. The proposed estimator is compared against different performance indexes, including the Unscented Kalman filter (UKF), unscented Kalman filter with parameter adaptation (PA), Extended Kalman Filter (EKF), Kalman filter with open-circuit voltage (OCV), Particle Filter (PF), and H-infinity estimator. This comparison was conducted using discharge profiles under different experimental conditions, where the SOCE herein proposed leads to the lowest error among all documented indexes and a performance improvement between 5.53 [%] and 99.90 [%]. Similarly, SOCE facilitates the characterization of the model inputs, reducing the preprocessing time while improving the execution time by 37 [%], and its estimation error by up to 86.77 [%]. These features enable the robust online implementation of embedded systems, improving SOC estimation.

Fabrication of pouch cell supercapacitors using abundant coal feedstock and their hybridization with Li-ion battery for e-rickshaw application

The environmental concerns and market demands created high demands of electric vehicles (EVs), but still the energy storage systems are lagging behind the fuel-based vehicles. Even though recent development in battery technologies bring forth great opportunities for EVs, the necessity and a good supply chain of electrode materials, does not fulfill the requirement of EVs. In India, battery-operated e-rickshaws face challenges like insufficient charging facility, low driving range, high battery cost, battery replacement, and disposal. To address the power delivery issues, we have designed and developed an indigenous Hybrid Battery Management System (HBMS) using fabricated coal-based supercapacitors and commercial Li-ion batteries for application in an e-rickshaw. For this study, we have fabricated 500 F pouch cell supercapacitors using high quality activated carbon derived from low-grade coal feedstock which shows excellent properties comparable to the commercially available supercapacitors. Five coal-based pouch cell supercapacitors (500 F) were connected through series parallel combination with commercial supercapacitor (Greencap. 500 F) to make a complete supercapacitor pack of 25 F and 54 V suitable for testing in the e-rickshaw (48 V and 1 kW motor). After implementing the developed hybridized battery management system (HBMS) in e-rickshaw, it showed the maximum speed of 45 km/h with additional power gain of 433 W. The analysis of data showed that the application of coal-based supercapacitors along with Li-ion battery had improved the overall performance of the e-rickshaw. Thus, this study has opened up a new venture of using abundant coal powder in fabricating low-cost pouch cell supercapacitor for using in EVs in a sustainable way that can influence the existing commercial battery market.

SOC Balancing Control Based on Predictive Power Model Amongst Supercapacitor Packs in MMC With Embedded Energy Storage System

Modular multilevel converter with supercapacitor (SC) packs-based energy storage system (MMC-SESS) can play a role in energy transition and renewable energy consumption. However, SESS's imbalance problem is caused by the inconsistency of its packs, which has a negative effect on the utilization of the MMC-SESS and has become a hot research topic. Confronting this problem, this paper proposes a state of charge (SOC) balancing control strategy amongst SC packs based on a discrete time-domain predictive power model in MMC-SESS based medium-voltage direct-current (MVDC). It is a double-loop control to accurately control the charging and discharging power. The outer power control establishes a discrete time-domain predictive power model for the SOC differences. The inner current loop designs a hybrid controller based on the continuous control set-model prediction control (CCS-MPC) and the feedback control strategy to accurately track the dynamic current reference. Simulations in PSCAD/EMTDC have shown that the proposed control can achieve SOC balancing amongst SC packs and improve the dynamic response as well as mitigate the SC pack current ripples.

A dynamic programming-optimized two-layer adaptive energy management strategy for electric vehicles considering driving pattern recognition

To achieve optimal real-time power allocation in electric vehicles, a two-layer adaptive dynamic programming (DP) optimization energy management strategy (EMS) has been proposed. The upper layer uses learning vector quantization (LVQ) to produce real-time driving pattern recognition (DPR) results. The method determines 10 characteristic parameters for training the recognition network and the length of the sampling window is 120 s. The typical driving cycles are divided into different levels of blocks to identify the real-time DPR level. The lower layer adopts the optimization strategy of DP extraction to adjust the power distribution between the battery pack and the supercapacitor pack according to the recognition results. DP is used to define a cost function to minimize the energy loss of the hybrid energy storage system (HESS) and optimize the battery usage range in the system. The near-optimal real-time EMS is extracted by analyzing the DP control behavior of the battery under the layered state of charge (SOC). The simulation results indicate that the proposed new rule control based on DP optimization (NRB) EMS improves the system efficiency by 10 % compared with the original rule-based (RB) EMS under different temperatures and DPR levels. In addition, the system efficiency gap is controlled at 3 % compared with DP.

Optimal charging of supercapacitors with user-specified charging time

Optimal charging of supercapacitors with energy efficiency maximization is of significance for supercapacitor charging systems. However, most existing studies are focused on the optimal charging of a single supercapacitor. In practical applications, supercapacitors are usually connected in series as packs. To address this problem, an optimal charging method is proposed for series-connected supercapacitor packs. By using it, the charging time can be specified by the user. Firstly, the existing charging methods for supercapacitor systems and their limitations are analyzed, especially when the charging time is limited. Then, a user-specified optimal charging method for supercapacitors with the user-specified charging time is designed, and the effectiveness of the proposed method in energy effectiveness maximization is rigorously proved. The performance of the proposed charging method is verified via extensive experimental results. The results show that the proposed charging method can effectively improve the energy efficiency under the limitation of charging time compared with the existing methods.

Design a Hybrid Energy-Supply for the Electrically Driven Heavy-Duty Hexapod Vehicle

Increasing the power density and overload capability of the energy-supply units (ESUs) is always one of the most challenging tasks in developing and deploying legged vehicles, especially for heavy-duty legged vehicles, in which significant power fluctuations in energy supply exist with peak power several times surpassing the average value. Applying ESUs with high power density and high overload can compactly ensure fluctuating power source supply on demand. It can avoid the ultra-high configuration issue, which usually exists in the conventional lithium-ion battery-based or engine-generator-based ESUs. Moreover, it dramatically reduces weight and significantly increases the loading and endurance capabilities of the legged vehicles. In this paper, we present a hybrid energy-supply unit for a heavy-duty legged vehicle combining the discharge characteristics of lithium-ion batteries and peak energy release/absorption characteristics of supercapacitors to adapt the ESU to high overload power fluctuations. The parameters of the lithium-ion battery pack and supercapacitor pack inside the ESU are optimally matched using the genetic algorithm based on the energy consumption model of the heavy-duty legged vehicle. The experiment results exhibit that the legged vehicle with a weight of 4.2 tons can walk at the speed of 5 km/h in a tripod gait under a reduction of 35.39% in weight of the ESU compared to the conventional lithium-ion battery-based solution.

Optimal sizing method with sensitivity analysis for hybrid energy storage system in electric vehicle using hybrid technique

This manuscript proposes a hybrid method for optimum sizing and energy management (EM) of hybrid energy storage systems (HESSs) in Electric vehicle (EV). The proposed hybrid method is combined performance of Honey Badger Algorithm (HBA) and recalling-enhanced recurrent neural network (RERNN), commonly called HBA-RERNN method. The major objective of proposed system is reducing the vehicle life time cost. The HESSs are incorporated with battery and super capacitor (SC). The proposed method is utilized to solve combined energy management and optimization size. Based on the variables, such as size of battery pack and super capacitor pack, HESS size is reflected. Depend on various sensitivity factors, optimum hybrid energy storage systems size and financial costs are analyzed. At last, the performance of proposed system is implemented on MATLAB site and compared with several existing systems. From this simulation outcome, it concludes that the proposed system diminishes the overall cost and battery degradation cost as 66625 USD than the existing systems. The efficiency of the proposed system achieves 94.8763%.

Organic Supercapacitors as the Next Generation Energy Storage Device: Emergence, Opportunity, and Challenges.

Harnessing new materials for developing high-energy storage devices set off research in the field of organic supercapacitors. Various attractive properties like high energy density, lower device weight, excellent cycling stability, and impressive pseudocapacitive nature make organic supercapacitors suitable candidates for high-end storage device applications. This review highlights the overall progress and future of organic supercapacitors. Sustainable energy production and storage depend on low cost, large supercapacitor packs with high energy density. Organic supercapacitors with high pseudocapacitance, lightweight form factor, and higher device potential are alternatives to other energy storage devices. There are many recent ongoing research works that focus on organic electrolytes along with the material aspect of organic supercapacitors. This review summarizes the current research status and the chemistry behind the storage mechanism in organic supercapacitors to overcome the challenges and achieve superior performance for future opportunities.

A hybrid energy storage solution based on supercapacitors and batteries for the grid integration of utility scale photovoltaic plants

This paper presents a 2-level controller managing a hybrid energy storage solution (HESS) for the grid integration of photovoltaic (PV) plants in distribution grids. The HESS is based on the interconnection of a lead-acid battery pack and a supercapacitor pack through a modular power electronics cabinet. The inclusion of the HESS into the PV plant –and not an state-of-the-art energy storage system based on a single technology–, is motivated by the diversity of technical requirements for the provision of the services of grid peak power shaving and PV output power ramp limitation. The 2-level controller ensures a synergistic exploitation of the two storage technologies aiming for an optimal service level of the HESS and minimum battery degradation. The higher level of the controller is based on a mathematical optimization problem that solves with the optimal schedule of the storage technologies for peak power shaving purposes. The power setpoints of this optimization are then complemented by a real time controller managing PV plant output ramp limitation. The HESS performance and associated controller has been proved effective through two case studies. The first one adopts a 6.6 MW PV plant including a HESS solution combining a 5.5 MWh and 2.64 MW lead-acid battery pack with a 0.25 MWh and 1.32 MW supercapacitor pack. The second one reports experimental data from an analogous scenario scaled down to kW level and using a laboratory scale prototype for the HESS. All in all, the hardware and software solutions proposed in this paper contribute to a feasible exploitation of multi-purpose energy storages targeting the needs of renewables' and distribution system operators.

A Grid-Connected Microgrid Model and Optimal Scheduling Strategy Based on Hybrid Energy Storage System and Demand-Side Response

The power gap between supply and demand in the microgrid caused by the uncertainty of wind and solar output and users’ electricity consumption needs to be absorbed by the hybrid energy storage devices and the demand-side electricity price response. To maximize the service life of the lithium battery pack, this paper optimizes a reasonable ratio of the supercapacitor pack’s daily charge and discharge times to the daily cycle times of the lithium battery pack. The model construction includes two parts: power prediction and multi-objective optimization modeling. In the case study, a microgrid district under the Guizhou Power Grid is analyzed and discussed. Based on the predicted wind output, solar output, and load demand on a certain day, the optimal scheduling results have been obtained. On the one hand, a reasonable ratio regarding the daily charge and discharge times of hybrid energy storage devices has been obtained under the optimized parameter k in the model. Correspondingly, the daily operation and maintenance of the lithium battery pack is minimum. On the other hand, when the hybrid energy storage devices and demand-side electricity price response are included and not, the changes on the supply and demand sides (a) and of three evaluation indicators (b) are compared, respectively. Thus, the effectiveness of the model in this paper is verified.

Modeling a residential grid-connected PV system with battery–supercapacitor storage: Control design and stability analysis

The increased penetration of renewables and the variable behavior of solar irradiation makes the energy storage important for overcoming several stability issues that arise in the power network. The current paper examines the design and stability analysis of a grid-connected residential photovoltaic (PV) system with battery–supercapacitor hybrid energy storage. The battery and supercapacitor packs are connected to the common 400 V DC-bus in a fully active parallel configuration through two bidirectional DC–DC converters, hence they have different voltage levels and their power flow is controlled separately. A detailed small-signal stability analysis is considered for the design of the current controllers for the bidirectional converters of the battery and supercapacitor. An important contribution here is that a detailed stability analysis is performed for both the boost and the buck mode of operation for the battery and supercapacitor converters, resulting in more accurate tuning of the controllers. Moreover, the small-signal stability analysis of the voltage source inverter (VSI) is considered in order to design the DC-bus voltage controller, where a reference output current is obtained using a phase-locked loop (PLL) for grid synchronization. The proposed model is developed and simulated in the MATLAB/Simulink software environment, based on mathematical analysis and average modeling. The simulation results verify the dynamic performance of the proposed model, through several rapid changes in PV generation and in load demand. Also, the model works properly and responds extremely fast during different mode transitions, exhibiting a very fast DC-bus voltage regulation with a very small ripple voltage (a maximum of ± 0.625%). Finally, the supercapacitor handles the rapid changes occurring within 0.2 s, hence this can relieve the battery stress and extend the battery lifetime.

Energetic Performances Booster for Electric Vehicle Applications Using Transient Power Control and Supercapacitors-Batteries/Fuel Cell

In this paper, a hybrid electric power supply system for an electric vehicle (EV) is investigated. The study aims to reduce electric stress on the main energy source (fuel cell) and boost energetic performances using energy sources with high specific power (supercapacitors, batteries) for rapid traction chain solicitations such as accelerations, decelerations, and braking operations. The multisource EV power supply system contains a fuel cell stack, a lithium batteries module, and a supercapacitors (Sc) pack. In order to emulate the EV energy demand (wheels, weight, external forces, etc.), a bidirectional load based on a reversible current DC-DC converter was used. Fuel cell (Fc) stack was interfaced by an interleaved boost converter. Batteries and the Sc pack were coupled to the DC point of coupling via buck/boost converters. Paper contribution was firstly concentrated on the distribution of energy and power between onboard energy sources in consonance with their dynamic characteristics (time response). Second contribution was based on a new Sc model, which takes into consideration the temperature and the DC current ripples frequency until 1000 Hz. Energy management strategy (EMS) was evaluated by simulations and reduced scale experimental tests. The used driving cycle was the US Federal Test Procedure known as FTP-75.

Multiport bidirectional DC–DC converter for PV powered electric vehicle equipped with battery and supercapacitor

This study presents a novel quasi-Z-source converter integrated isolated multiport bidirectional DC–DC converter topology for a photovoltaic (PV) powered and battery/supercapacitor buffered electric vehicle (EV). The proposed topology can provide uninterrupted power to the electric motor of EV and regain the braking energy with the capability of bidirectional power flow. The system integrates quasi-Z-source and H-bridge converters with an existing switch. Thus, a four-port converter is achieved without any need for individual converters or additional switches. Besides, the high-gain quasi-Z-source converter allows the reduction of the rated voltages of the battery and supercapacitor packs, as well as allows using a high-frequency transformer (HFT) with a low turn ratio. The isolation between ports is provided by a secondary centre-tapped HFT. The secondary side of the HFT is equipped with a controlled full-wave rectifier to provide bidirectional power flow. In addition, a power flow management and corresponding control scheme are suggested. The performance of the proposed system has been evaluated for different operational changes. Results show that it properly performs the power flow between the ports under steady-state and transient conditions. The power flow capabilities and efficiency values validate the viability and effectiveness of the proposed system.

A comparison of real-time energy management strategies of FC/SC hybrid power source: Statistical analysis using random cycles

This paper presents a comparative study of two promising real-time energy management strategies for fuel cell electric vehicle applications: adaptive equivalent consumption minimization strategy (A-ECMS), and stochastic dynamic programming (SDP). An off-line algorithm –classic dynamic programming - provides reference results. On-line and off-line strategies are tested both in simulation and using a dedicated test bench completely consistent with an electric scooter powertrain.The hybrid power source combines a fuel cell, a supercapacitor pack and two related power converters. The system model is carefully calibrated using experimental data. This allows meaningful identification of parameters of the various strategies. The model data is determined using a motorcycle certification driving cycle.The robustness of each strategy is then analyzed using a large number of random driving cycles. Experimental and simulation results show that a specific SDP approach, based on Markov chain modeling, has the best overall performance in real-world driving conditions. It achieves the minimum average hydrogen consumption while respecting the state-sustaining constraint. Conversely, the A-ECMS results lack robustness and show poor performance indexes when facing unknown real world power demand profile. In conclusion, the present results indicate SDP is an interesting approach for future hybrid source energy allocation.

Applications of battery/supercapacitor hybrid energy storage systems for electric vehicles using perturbation observer based robust control

This paper designs a robust fractional-order sliding-mode control (RFOSMC) of a fully active battery/supercapacitor hybrid energy storage system (BS-HESS) used in electric vehicles (EVs), in which two bidirectional DC/DC converters are employed to decouple battery pack and supercapacitor pack from DC bus based on the classical 5th-order averaged model. Rule-based strategy (RBS) is firstly employed as the energy management strategy (EMS) to generate the battery current reference. Then, RFOSMC scheme is developed as the underlying controller to globally compensate nonlinearities and various uncertainties of BS-HESS by the real-time perturbation estimation via a sliding-mode state and perturbation observer (SMSPO). Two outputs are chosen, e.g., battery current and DC bus voltage, which are also the only states that need to be measured for the control system design, thus RFOSMC is relatively easy to be implemented. The control performance of RFOSMC is thoroughly investigated in comprehensive case studies to that of other three typical controllers. Finally, a hardware-in-the-loop (HIL) test is undertaken to validate the effectiveness of the proposed control scheme.

Evaluation of fluctuating voltage topology with fuel cells and supercapacitors for automotive applications

To develop a single-stage power conversion topology in which energy storage devices can be directly coupled, a fluctuating voltage topology is applied, leading to lower cost and more compactness with the absence of DC/DC converters. This paper investigates such a topology for automotive applications where fuel cells are directly connected to the DC bus of the inverter, resulting in fluctuating voltage across the DC bus. Further, a supercapacitor pack is also introduced to maintain the power capacity and voltage stability. The hybridization principle and practical application of such a topology are then discussed in the time domain and frequency domain. Furthermore, the transient power requirement is decomposed to design the size of fuel cells and supercapacitors. Simulation results from the modeling of the fuel cell-supercapacitor powertrain demonstrate the feasibility and effectiveness of this topology. The supercapacitors can serve as a low-pass filter for the fuel cells. In conclusion, the peak power requirement can be successfully achieved because of the lowered system impedance, and the fuel cells only need to supply the average power.

Experimental Study on a Semi-Active Battery-Supercapacitor Hybrid Energy Storage System for Electric Vehicle Application

This paper presents an experimental study on a semi-active hybrid energy storage system consisting of a battery pack and a supercapacitor pack for electric vehicle application. First, a real-time energy management control strategy based on a combination of filtering and fuzzy logic controller is proposed. The main advantage of the proposed control strategy is that the peak current of the battery can be obviously reduced while ensuring the voltage of the supercapacitor fluctuates within a certain desired range. Second, a 30 kW rated power experimental platform is constructed, in which only one dc/dc converter is used to regulate the power flow between the battery and the supercapacitor. Finally, a corrected battery fade model, which can accurately match the studied battery, is used to analyze the battery fade behavior. The results reveal that the battery capacity fade cost of the hybrid energy storage system can be reduced by 44.42%, 30.44%, and 57.16% compared with the sole battery storage under new European drive cycle, highway driving cycle, and Indian urban driving cycle, three driving cycles, respectively.

A Supercapacitor-Based Method to Mitigate Overvoltage and Recycle the Energy of Pantograph Arcing in the High Speed Railway

The pantograph arcing phenomenon may shorten the service life of a pantograph and even destroy onboard devices and instruments, due to the irregular motions of the train and the intermittent line–pantograph disconnection. This paper points out that abrupt inductive energy from the magnetizing inductance of the traction transformer can lead to an electromagnetic transient process with unexpected overvoltage across it. Further, a supercapacitor-based power electronic system is proposed, which can not only redirect the inductive energy to the supercapacitor pack through bidirectional converters but also mitigate the overvoltage across the main electrical equipment when pantograph arcing occurs. Simulation results show the overvoltage could be reduced and the energy stored in the supercapacitor which could also be used to provide energy for sensors or other devices.