Ultracapacitor Hybrid Research Articles

Particle Swarm-Optimized Fuzzy Logic Energy Management of Hybrid Energy Storage in Electric Vehicles

A lithium-ion battery–ultracapacitor hybrid energy storage system (HESS) has been recognized as a viable solution to address the limitations of single battery energy sources in electric vehicles (EVs), especially in urban driving conditions, owing to its complementary energy features. However, an energy management strategy (EMS) is required for the optimal performance of the HESS. In this paper, an EMS based on the particle swarm optimization (PSO) of the fuzzy logic controller (FLC) is proposed. It aims to minimize battery current and power peak fluctuations, thereby enhancing its capacity and lifespan, by optimizing the weights of formulated FLC rules using the PSO algorithm. This paper utilizes the battery temperature as the cost function in the optimization problem of the PSO due to the sensitivity of lithium-ion batteries (LIBs) to operating temperature variations compared to ultracapacitors (UCs). An evaluation of optimized FLC using PSO and a developed EV model is conducted under the Urban Dynamometer Driving Schedule (UDDS) and compared with the unoptimized FLC. The result shows that 5.4% of the battery’s capacity was conserved at 25.5 °C, which is the highest operating temperature attained under the proposed strategy.

AUTONOMOUS MOBILE ROBOT WITH HYBRID PEM FUEL-CELL AND ULTRACAPACITORS ENERGY SYSTEM. DEDALO 2.0

This paper presents a hybrid configuration combining a hydrogen fuel cell and ultracapacitors to create an energy storage system. Hybrid topology is constructed using a SEPIC converter, which connects the fuel cell with the DC bus whereas a bidirectional Buck-Boost converter links the ultracapacitors group with the DC bus. The main aim is to increase the efficiency of the hybrid power system applied about an autonomous mobile robot. An active Fuel Cell voltage control strategy is presented to manage the power flows. In addition, the overall efficiency of the proposed hybrid power system at overload operation is higher than the conventional one. In this paper, an autonomous mobile robot was converted from a conventional lead-acid or lithium-ion battery to a hybrid PEM Fuel-Cell and ultracapacitors as the power source. The integration of UCaps as element of energy storage on the robot was studied with the aim to improve the energetic solution

Energy Management Strategy Based on Model Predictive Control‐Differential Evolution for Hybrid Energy Storage System in Electric Vehicles

This paper addresses challenges related to the short service life and low efficiency of hybrid energy storage systems. A semiactive hybrid energy storage system with an ultracapacitor and a direct current (DC) bus directly connected in parallel is constructed first, and then related models are established for the lithium‐ion battery, system loss, and DC bus. Based on the multiobjective evaluation function, a hybrid energy storage system Model Predictive Control‐Differential Evolution (MPC‐DE) energy management method is proposed. Experiments were conducted under China Light‐Duty Vehicle Test Cycle‐Passenger Car (CLTC‐P) and Highway Fuel Economy Test (HWFET) driving cycles. The experimental results show that compared with other methods, this strategy can effectively reduce the loss of lithium‐ion battery and ultracapacitor hybrid energy storage system and improve the system efficiency.

Slime Mould Algorithm (SMA) and Adaptive Neuro-Fuzzy Inference (ANFIS)-Based Energy Management of FCHEV Under Uncertainty

This manuscript proposes a hybrid technique for optimal energy management (EM) of fuel cell (FC) and ultra-capacitor (UC) hybrid electric vehicles (FCHEVs) under uncertainty. The proposed method is a joint execution of the Slime Mould Algorithm (SMA) and the Adaptive Neuro-fuzzy Inference System (ANFIS), otherwise called the SMA-ANFIS system. The main aim of the proposed system is to achieve and regulate the steady state of DC bus voltage with minimal steady-state error (SSE) under different load conditions by using the proposed SMA-ANFIS technique. FC supplies power during vehicular operation and it is used to regulate DC bus voltage to the chosen value and recharge, and UC supplies current optimally through the proposed technique. The optimal EMS performs and controls the power flows through the associated power converters to accomplish some power allocation and energy efficiency levels. Finally, the proposed method is done in the MATLAB platform, and the performance is compared with other methods.

Test bench setup for emulating electric vehicle on-road conditions

This work provides an electric vehicle (EV) test bench with a motor/dynamometer setup with a battery and ultracapacitor (UC) hybrid energy storage. Extending the driving range and enhancing the battery life are the main concerns with EVs nowadays. The drive motor (DM) used is a three-phase induction motor (IM), which is controlled by the current sensorless indirect vector control method. This fault-tolerant method can be used in the case of current sensor failure. All the resistive forces acting on an EV are emulated based on the concept of vehicle equivalent rotational inertia for different real-life driving cycles, namely ECE R15 and NYCC. The battery alone is not capable of handling the surge current requirement during the acceleration period and is not able to capture the total power during regenerative breaking as it has a low power density. Hence, a high power density source like UC is a must to handle these conditions during frequent stop and go city traffic conditions as per ECE R15 and NYCC driving cycles. This EV emulation technique helps in getting the DC-link power profile for an EV for any driving scenario. Hence, it is possible to test the different powertrain components of an EV using this proposed technique.

Design of Metaheuristic Optimization with Deep-Learning-Assisted Solar-Operated On-Board Smart Charging Station for Mass Transport Passenger Vehicle

Electric vehicles (EVs) have become popular in reducing the negative impact of ICE automobiles on the environment. EVs have been predicted to be an important mode of mass transit around the globe in recent years. Several charging stations in island and remote areas are dependent on off-grid power sources and renewable energy. Solar energy is used in the daytime as it is based on several environmental components. The creation of efficient power trackers is necessary for solar arrays to produce power at their peak efficiency. To deliver energy during emergencies and store it in case there is an excess, energy storage systems are required. It has long been known that reliable battery management technology is essential for maintaining precise battery charge levels and avoiding overcharging. This study suggests an ideal deep-learning-assisted solar-operated off-board smart charging station (ODL-SOOSCS) design method as a result. The development of on-board smart charging for mass transit EVs is the main goal of the ODL-SOOSCS technique that is being described. In the ODL-SOOSCS approach described here, a perovskite solar film serves as the generating module, and the energy it generates is stored in a module with a hybrid ultracapacitor and a lithium-ion battery. Broad bridge converters and solar panels are incorporated into the deep belief network (DBN) controller, which doubles as an EV charging station. An oppositional bird swarm optimization (OBSO) algorithm is used as a hyperparameter optimizer to improve the performance of the DBN model. Moreover, an MPPT device is exploited for monitoring and providing maximal output of the solar panel if the power sources are PV arrays. The proposed system combines the power of metaheuristic optimization algorithms with deep learning techniques to create an efficient and smart charging station for mass transport passenger vehicles. This integration of two powerful technologies is a novel approach toward solving the complex problem of charging electric vehicles in mass transportation systems. The experimental validation of the ODL-SOOSCS technique is tested on distinct converter topologies. A widespread experimental analysis assures the promising performance of the ODL-SOOSCS method over other current methodologies.

Cost minimization oriented energy management of PV-assisted refueling and recharging stations for FC-ultracapacitor hybrid trams

Fuel cell (FC) and ultracapacitor hybrid trams offer a sustainable and efficient transportation option, with the ability to store and use renewable energy for propulsion. However, their widespread adoption is limited by the availability of reliable and cost-effective refueling and recharging infrastructure. In this study, the use of mixed-integer linear programming (MILP) optimization for the energy management of photovoltaic (PV)-assisted refueling and recharging stations for fuel cell ultracapacitor hybrid trams is investigated. The electrolyzers and recharging units can either be supplied by the grid or by PV, depending on the availability of renewable energy.The study's main contribution is the consideration of the tram-station and internal tram transactions in a single optimization-based energy management structure and the all-in-one renewable energy assisted refueling and recharging station concept, which considers both the hydrogen and electricity supply requirements. The proposed structure was tested using the data of the Istanbul Kabataş-Bağcılar tram line, and the results showed a 46.48% reduction in operating cost and a significant decrease in carbon dioxide emissions and power drawn from the grid. The study provides valuable information for rail system operators and state authorities and opens up possibilities for future studies in the integration of hydrogen fuel cell vehicles into refueling stations.

Bio-Waste Derived Honeycomb Structured Activated Carbons as Anode Materials for Lead-Carbon Hybrid Ultracapacitors

Lead-carbon hybrid ultracapacitors (Pb-C HUC) are the solution to the sulfation issue of lead-acid batteries. The Pb-C HUCs are of much interest due to the aqueous system with longer cycle life and higher power density. Here, honeycomb structured porous activated carbons with 1790 m2 g−1 of surface area were synthesized from Carica papaya biowaste by chemical treatment followed by carbonization at 800 °C (PAC-800). PAC-800 composite electrode delivers a specific capacitance of 250 F g−1 at 1 Ag−1 and has 10000 stable cycle life in 4.5 M H2SO4. Further, a kinetic study of the PAC-800 electrode illustrates that at 2 mV s−1, they show 61% of capacitive and 39% of pseudocapacitive charge storage. Pb-C HUCs fabricated using in situ activated PbO2 sheet as cathode and PAC-800 composite electrode as anode delivers 390 F g−1 at 1 A g−1 and have 93% capacitance retention over 15000 cycles at 5 A g−1. Further, the current Pb-C HUC results are compared with commercially available high surface area (2484 m2 g−1) carbons based Pb-C HUCs. This work illustrates an easy, scalable synthesis root for biowaste carbons and their electrochemical performance in Pb-C HUCs, which is on par with commercial high surface area carbons.

Electrochemically Exfoliated Layered Carbons as Sustainable Anode Materials for Lead Carbon Hybrid Ultracapacitor

AbstractLead‐carbon hybrid ultracapacitors (Pb−C HUC) have become apparent as a way out of the sulfation issue of lead‐acid batteries, simultaneously enhancing the system‘s power density and cycle life. In this work, exfoliated graphene oxides (EGO) were synthesized by the electrochemical exfoliation method followed by chemical activation and carbonization at 600 °C (AEGO‐600). The composite electrode delivered 800 F g−1 capacitance at 1 A g−1. The Pb−C HUC fabricated using AEGO‐600 anode and PbO2 cathode can achieve capacitance of 325 F g−1 at 10 A g−1 and retain 71 % capacitance after 15000 charge‐discharge cycles in the voltage range of 2.3–0.8 V. The highly stable capacitance was due to the formation of layered carbons in AEGO‐600 that enhanced the favorable electrolyte ion assessment to maximum active sites. Owing to the facile, cost‐effective synthesis approach and better charge storage behavior, the activated‐exfoliated graphene oxides thus produced could be suitable candidates for future hybrid ultracapacitor systems.

Lead–carbon hybrid ultracapacitors fabricated by using sulfur, nitrogen-doped reduced graphene oxide as anode material derived from spent lithium-ion batteries

Lead–carbon hybrid ultracapacitors fabricated by using sulfur, nitrogen-doped reduced graphene oxide as anode material derived from spent lithium-ion batteries

Bio‐waste derived carbon nano‐onions as an efficient electrode material for symmetric and lead‐carbon hybrid ultracapacitors

Carbon and metal oxide nanocomposites have been extensively studied as electrode materials to develop energy and power-dense supercapacitors in recent years. Nevertheless, nano carbons with improved porosity and functional moieties are the most eco-friendly and cost-effective supercapacitor materials. In this work, carbon nano-onions (CNOs) synthesized by a single-step flame soot collection method, subsequently calcined at 600°C in an inert environment (CNO-600), are used as electrode material for the supercapacitors. CNO-600 s have a layer-by-layer nano onion structure with a ~25 nm particle size and a Brunauer–Emmett–Teller surface area of 147 m2 g−1. CNO-600 delivers 266 and 186 F g−1 of capacitance at 0.5 A g−1 for half cells and symmetric ultracapacitors, respectively. Ultracapacitors show capacitance retention of 91% with 20 000 GCD cycles in 1 M H2SO4 electrolyte. The stable capacitance of CNO-600 is due to easy intercalation/de-intercalation of electrolyte ions and electrons in the layer-by-layer structure of CNOs, contributing to pseudocapacitive charge storage with electric double layer capacitor behavior. The lead-carbon hybrid ultracapacitor fabricated using CNO-600 as anode material and PbO2 as cathode delivers a specific capacitance of 515 F g−1 at 1 A g−1 in 4.5 M H2SO4 electrolyte in the voltage range of 2.3 and 0.6 V. The substantial improvement of charge storage in CNO-based symmetric and lead-carbon hybrid system, demonstrate an excellent opportunity for the development of high-performance supercapacitors.

Performance Analysis of Hybrid Ultra Capacitor (HUC) based Solar Microgrid for Household Applications

Localised power generation and consumption using a solar-based hybrid micro-grid system are gaining predominance in remote locations where conventional transmission of power from far off substations work out to be uneconomical. Since the peak irradiance from the sun lasts for 4-6 hours per day, a hybrid micro-grid with batteries for storing energy is usually adopted. This study considered a typical household load of 3kW comprising resistive and inductive loads. Sudden surges will be caused by switching ON/OFF of any load, and in particular, switching ON of inductive loads (such as fans, washing machines and mixer) will further contribute to transients. These sudden changes in loads harm the cyclic life of the battery. A viable solution to overcome the above problem is to use Hybrid Ultra Capacitors (HUC) as an assistant to the Batteries. These HUC banks can take over the surge loads, whereas Batteries can focus on delivering steady power. Such a combination has the potential to enhance the battery’s life. This study discusses the performance of Hybrid Ultra Capacitor (HUC) based Hybrid Energy Storage System (HESS) in a 3kW Solar MicrogriAU: Please prod system by evaluating the electrical parameters involving experiments with different loads.

Frequency splitting approach using wavelet for energy management strategies in fuel cell ultra-capacitor hybrid system

Using frequency splitting, two energy management strategies (EMS) based on Haar wavelet decomposition and Fourier analysis for fuel cell hybrid vehicle (FCHV) are proposed to manage efficiently the power flow between components. The paper aims to discuss the performances of the proposed EMS in terms of dynamic behavior, robustness operation, real time application and fuel economy. For apply this methodology, two EMS approaches are elaborated and successfully tested for parallel Fuel Cell/UC: conventional approach using Fourier Transform analysis (FT) and Wavelet analysis approach allowing natural frequency splitting. Finally, and to evaluate the performance and relevance of the developed approach, a comparison analysis were conducted. The simulation results exhibit the effectiveness of both strategies. Indeed, Wavelet analysis leads to better results in terms of energy flow and dynamic behavior, excellent robustness and stability of system, as well as energy economy improvement. A very relevant strategy is proposed based on Wavelet analysis using digital filtering techniques, which enables a natural frequency splitting to ensure the best global performances. In addition, the approach remains simple and suitable for real time operation.

Sizing optimization research considering mass effect of hybrid energy storage system in electric vehicles

This paper uses dynamic programming to deal with the sizing optimization problem for battery/ ultracapacitor hybrid energy storage systems in electric vehicles to minimize the electricity cost and battery degradation cost. The sizing of the battery pack is designed to meet the minimum mileage of electric vehicles. The optimal sizing of the ultracapacitor pack is optimized by dynamic programming, especially considering the influence of ultracapacitor mass on the load power. Results show that the operation cost firstly decreases rapidly as the ultracapacitor number increases. After a turning point, the operation cost slowly increases due to the increasingly heavy ultracapacitors, thus the turning point is chosen as the optimal sizing result. Two different optimal sizing schemes for designing different vehicle types are proposed through results fusion under low, medium, and high-speed driving conditions. Compared with sizing optimization results without load power changes due to ultracapacitor mass, the proposed optimal schemes add more ultracapacitor packs and can therefore reduce the vehicle operation cost by 3.94% to 6.54% under different driving conditions.

A Study of Control Methodologies for the Trade-Off between Battery Aging and Energy Consumption on Electric Vehicles with Hybrid Energy Storage Systems

Hybrid and electric vehicle batteries deteriorate from use due to irreversible internal chemical and mechanical changes, resulting in decreased capacity and efficiency of the energy storage system. This article investigates the modeling and control of a lithium-ion battery and ultracapacitor hybrid energy storage system for an electric vehicle for improved battery lifespan and energy consumption. By developing a control-oriented aging model for the energy storage components and integrating the aging models into an energy management system, the trade-off between battery degradation and energy consumption can be minimized. This article produces an optimal aging-aware energy management strategy that controls both battery and ultracapacitor aging and compares these results to strategies that control only battery aging, strategies that control battery aging factors but not aging itself, and non-optimal benchmark strategies. A case study on an electric bus with variously-sized hybrid energy storage systems shows that a strategy designed to control battery aging, ultracapacitor aging, and energy losses simultaneously can achieve a 28.2% increase to battery lifespan while requiring only a 7.0% decrease in fuel economy.

Polypyrrole-MoS2 Nanopetals as Efficient Anode Material for Lead-Based Hybrid Ultracapacitors

Lead-carbon hybrid ultracapacitors are being a solution to the lead-acid battery to solve issues of sulfation and improve cycle life. In this work, we present polypyrrole-MoS2–based composite anode material coupled with PbO2 cathode for the lead-carbon hybrid ultracapacitors. Ultracapacitor behavior of polypyrrole-MoS2 based composite shows significant improvement in capacitance and power-density due to the synergetic effect of the high conducting polymer network and redox behavior of MoS2. The nanopetal shaped composite materials have been synthesized by a simple hydrothermal method at 160 oC by using polypyrrole. The composite Polypyrrole-MoS2 electrode delivers a specific capacitance of 782 Fg−1 at 1 A g−1 current density with low areal specificresistance (1.15 Ohm cm2) in an aqueous H2SO4 electrolyte. Besides, the PbO2/Polypyrrole-MoS2 hybrid ultracapacitors deliver capacitance of 285 F g−1 at 5 A g−1 and stable over 10,000 cycles. The improved capacitive behavior of the Polypyrrole-MoS2 composite electrode is due to the redox behavior, effective intercalation of H+ ions into the composite frameworks by transporting the electrons as well as have easy doping/de-doping of sulfate ions to the polypyrrole network.

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)

Improving battery state estimation accuracy through the addition of a series capacitor

This article is motivated by the theoretical bounds on battery state of charge estimation accuracy, particularly in the presence of biased and/or noisy current/voltage measurements. The main goal is to show that the addition of a series ultracapacitor improves these theoretical bounds, enabling more accurate state estimation. The authors derive this conclusion analytically by employing Fisher information analysis to show that the Cramér–Rao bounds on estimation accuracy are significantly smaller for a hybrid ultracapacitor–battery system compared to a battery-only system. The addition of series capacitance furnishes this improvement in estimation accuracy by increasing sensitivity of the ultracapacitor–battery open-circuit potential to changes in stored charge. This makes the proposed pack hybridization concept particularly attractive for battery chemistries where the slope of battery voltage versus charge can be very small, e.g., LiFePO4 cells. Monte Carlo simulation studies support this theoretical insight, for both linearized and nonlinear LiFePO4 battery models. The simulation results also provide the important added observation that in situations where model mismatch introduces estimation bias, the use of ultracapacitor–battery hybridization reduces this bias. Moreover, experimental validation is performed in this article. Both the simulation and test results confirm the improvements in estimation variance predicted by Fisher analysis for unbiased estimators.

On the Hybridization of Microcars with Hybrid UltraCapacitors and Li-Ion Batteries Storage Systems

The objective proposed by the EU to drastically reduce vehicular CO2 emission for the years up to 2030 requires an increase of propulsion systems’ efficiency, and accordingly, the improvement their technology. Hybrid electric vehicles could have a chance of achieving this, by recovering energy during braking phases, running in pure electric mode and allowing the internal combustion engine to operate under better efficiency conditions, while maintaining traditionally expected vehicle performances (mileage, weight, available on-board volume, etc.). The energy storage systems for hybrid electric vehicles (HEVs) have different requirements than those designed for Battery Electric Vehicles (BEVs); high specific power is normally the most critical issue. Using Li-ion Batteries (LiBs) in the designing of on-board Energy Storage Systems (ESS) based only on power specifications gives an ESS with an energy capacity which is sufficient for vehicle requirements. The highest specific power LiBs are therefore chosen among those technologically available. All this leads to an ESS design that is strongly stressed over time, because current output is very high and very rapidly varies, during both traction and regeneration phases. The resulting efficiency of the ESS is correspondingly lowered, and LiBs lifetime can be relevantly affected. Such a problem can be overcome by adopting hybrid storage systems, coupling LiBs and UltraCapacitors (UCs); by properly dimensioning and controlling the ESS’ components, in fact, the current output of the batteries can be reduced and smoothed, using UCs during transients. In this paper, a simulation model, calibrated and validated on an engine testbed, has been used to evaluate the performances of a hybrid storage HEV microcar under different operative conditions (driving cycles, environment temperature and ESS State of Charge). Results show that the hybridization of the powertrain may reduce fuel consumption by up to 27%, while LiBs lifetime may be more than doubled.

A review of key issues for control and management in battery and ultra-capacitor hybrid energy storage systems

Abstract The hybrid energy storage system is a kind of complex system including state coupling, input coupling, environmental sensitivity, life degradation, and other characteristics. How to accurately estimate the internal state of the system, delay the battery life degradation, realize the coordinated and optimized control of power and energy have become the focus and difficulty of the hybrid energy storage system. With the application and popularization of hybrid energy storage systems in electric vehicles and smart grids, relevant theoretical and technological breakthroughs become more and more urgent. Many new achievements, new theories, new methods and new technologies from the fields of materials, information, energy, control and artificial intelligence have been put into this field. This paper comprehensively reviewed the key issues for control and management in hybrid energy storage systems from the aspects of multi-scale state estimation, aging mechanism investigation, life prediction, and energy optimization control of the hybrid energy storage system. Through the in-depth review of key scientific issues, the latest theoretical techniques and application results are presented. Finally some future research challenges and outlooks are presented, in hopes to provide some new ideas and inspirations for the future investigation of the hybrid energy storage systems.