Composite Energy Storage System Research Articles

The Effect of Ultracapacitor on the Performance of Series Range-Extended Hybrid Commercial Vehicle

<div>Toward the goal of “dual carbon economy” development, new energy hybrid commercial vehicles have become the main vehicles to meet the future fuel consumption and emission targets. In order to meet the high requirements of commercial vehicles on power and to minimize the influence of ambient temperature on the power of the vehicle, this study proposes a composite energy storage system (CESS) incorporating ultracapacitors. To further understand the impact of ultracapacitor on the dynamic performance of the vehicle, this study compares the dynamics of series range-extended hybrid pickup trucks with and without ultracapacitor at ambient and low temperatures, as well as the effect of ultracapacitor on the service life of lithium-ion batteries, by means of simulation. The results show that at room temperature (25°C), the addition of ultracapacitor shortens the 0–100 km/h acceleration time of the whole vehicle by 24.4% and improves the off-road climbing performance by 11.7%; at low temperature (−20°C), the addition of ultracapacitor shortens the 0–100 km/h acceleration time of the whole vehicle by 88.8% and improves the off-road climbing performance by 67.9%. Under WLTC, 3% gradient conditions, the ultracapacitor increases the cycle life of the lithium-ion battery by about 9% and reduces heat generation by 11.7%.</div>

An energy management strategy with considering ultracapacitor ideal state of charge for fuel cell/battery/ultracapacitor vehicle

The hybridization of energy storage systems consisting of fuel cells, batteries, and ultracapacitors has tremendous potential in fuel cell hybrid electric vehicles. However, the utilization of ultracapacitors in existing energy management strategies is insufficient, preventing complete exploitation of the energy storage system's benefits. To strengthen the utilization of ultracapacitors, this paper proposes an energy management strategy for fuel cell vehicles with three energy sources, considering the ideal state of charge (SOC) of ultracapacitors. The proposed method disassembles the motor power demand, with the ultracapacitor primarily supplying the acceleration portion. It calculates the ideal SOC of the ultracapacitor, and controlling the actual SOC of the ultracapacitor to match the ideal SOC. Furthermore, a fuzzy logic controller is designed to modify the fuel cell's output power, reducing power fluctuation. Additionally, according to the variation of the SOC of the battery, the fuel cell output power is modified to enhance the overall performance of the composite energy storage system. Simulation and hardware-in-loop results demonstrate that, compared to the adaptive filtering strategy with fuel cell power constraints and dynamic programming strategy, the strategy proposed in this paper reduces operational costs by 14.56 % and 4.99 %, respectively.

Design of energy management for composite energy storage system consisting of lithium battery and flywheel based on adaptive wavelet–fuzzy control strategy

Design of energy management for composite energy storage system consisting of lithium battery and flywheel based on adaptive wavelet–fuzzy control strategy

Research on the capacity allocation of composite energy storage systems for hybrid ships

Abstract Aiming at the problem of unstable output power fluctuation of the dredger during operation, a composite energy storage system consisting of lithium iron phosphate battery and supercapacitor is introduced to smooth out the power fluctuation. Considering the configuration cost, operation and maintenance cost of the energy storage system, the capacity optimization model of the composite energy storage system is established with the average daily cost as the objective function, and with the system power balance, the charge state of the energy storage system, and the rated power as the constraints. The optimal capacity is solved by using the modified artificial fish swarm algorithm (MAFSA). The final results show that MAFSA reduces the capacity of the battery and the supercapacitor by 6.9% and 9.9%, respectively, and reduces the average daily cost of the system by 13.5%. Meanwhile, the capacity-optimized energy storage system enables the generator set to work in the optimal operating range, which reduces its output power fluctuation, improves its efficiency, and reduces fuel consumption and pollutant emission.

Analysis of the potential application of a residential composite energy storage system based on a double-layer optimization model

Along with the further integration of demand management and renewable energy technology, making optimal use of energy storage devices and coordinating operation with other devices are key. The present study takes into account the current situation of power storage equipment. Based on one year of measured data, four cases are designed for a composite energy storage system (ESS). In this paper, a two-tiered optimization model is proposed and is used to optimizing the capacity of power storage devices and the yearly production of the system. Furthermore, this paper performs a comparative analysis of the performance of the four cases from the energy, environmental and economic perspectives. It is concluded that this kind of energy storage equipment can enhance the economics and environment of residential energy systems. The thermal energy storage system (TESS) has the shortest payback period (7.84 years), and the CO2 emissions are the lowest. Coupled with future price volatility and the carbon tax, the electrothermal hybrid energy storage system (HESS) has good development potential. However, the current investment cost is very high, and it will not be possible to recover this cost in 10 years. Finally, it is recommended that the cost of equipment be reduced in combination with subsidies and incentives for further promotion. The research results not only fill a gap in the study area, but also provide some suggestions for further development of industry and research on user-side energy storage.

Research on Energy Hierarchical Management and Optimal Control of Compound Power Electric Vehicle

In response to the challenges posed by the low energy utilization of single-power pure electric vehicles and the limited lifespan of power batteries, this study focuses on the development of a compound power system. This study constructs a composite power system, analyzes the coupling characteristics of multiple systems, and investigates the energy management and optimal control mechanisms. Firstly, a power transmission scheme is designed for a hybrid electric vehicle. Then, a multi-state model is established to assess the electric vehicle’s performance under complex working conditions and explore how these conditions impact system coupling. Next, load power is redistributed using the Haar wavelet theory. The super capacitor is employed to stabilize chaotic and transient components in the required power, with low-frequency components serving as input variables for the controller. Further, power distribution is determined through the application of fuzzy logic theory. Input parameters include the system’s power requirements, power battery status, and super capacitor state of charge. The result is the output of a composite power supply distribution factor. To fully exploit the composite power supply’s potential and optimize the overall system performance, a global optimization control strategy using the dynamic programming algorithm is explored. The optimization objective is to minimize power loss within the composite power system, and the optimal control is calculated through interpolation using the interp function. Finally, a comparative simulation experiment is conducted under UDDS cycle conditions. The results show that the composite power system improved the battery discharge efficiency and reduced the number of discharge cycles and discharge current of the power battery. Under the cyclic working condition of 1369 s, the state of charge of the power battery in the hybrid power system decreases from 0.9 to 0.69, representing a 12.5% increase compared to the single power system. The peak current of the power battery in the hybrid power system decreases by approximately 20 A compared with that in the single power system. Based on dynamic programming optimization, the state of charge of the power battery decreases from 0.9 to 0.724. Compared with that of the single power system, the power consumption of the proposed system increases by 25%, that of the hybrid power fuzzy control system increases by 14.2%, and that of the vehicle decreases by 14.7% after dynamic programming optimization. The multimode energy shunt relationship is solved through efficient and reasonable energy management and optimization strategies. The performance and advantages of the composite energy storage system are fully utilized. This approach provides a new idea for the energy storage scheme of new energy vehicles.

Waste-derived thermal storage solutions for sustainable solar desalination using discarded engine oil and paraffin wax: A techno-environmental feasibility evaluation

The valorization and repurposing of waste materials for sustainable outcomes and environmental mitigation are gaining prominence. This investigation explores the feasibility of repurposing discarded automotive engine oil as a viable means of energy storage in solar thermal desalination applications. A novel approach combining discarded engine oil with Paraffin wax in equal parts by volume is proposed as a composite energy storage (CES) to enhance nocturnal production and efficiency. The experimental findings show that the composite energy storage system has 26.54 % higher thermal conductivity and 44.66 % greater specific heat energy storage capacity compared to pure paraffin wax. Comparing the Desalination System with Engine Oil-based Energy Storage (DSEES) to a Traditional Solar Desalination System (TSDS) without energy storage, considering water and absorber temperatures and distillate production, reveals compelling advantages. DSEES exhibits remarkable temperature increases of 14 % in the basin and 11 % in water, alongside a significant 52.72 % rise in distillate production rates, yielding 3.36 and 3.16 l/sq.mt compared to TSDS's 2.2 and 2.1 l/sq.mt over two testing days. Cost analysis indicates DSEES's 33.7 % lower cost per liter and 33.8 % shorter payback period relative to TSDS. Furthermore, environmental assessment highlights DSEES's 60.8 % greater net carbon credit, indicating reduced ecological impact.

Fuzzy Approach for Managing Renewable Energy Flows for DC-Microgrid with Composite PV-WT Generators and Energy Storage System

Recently, the implementation of software/hardware systems based on advanced artificial intelligence techniques for continuous monitoring of the electrical parameters of intelligent networks aimed at managing and controlling energy consumption has been of great interest. The contribution of this paper, starting from a recently studied DC-MG, fits into this context by proposing an intuitionistic fuzzy Takagi–Sugeno approach optimized for the energy management of isolated direct current microgrid systems consisting of a photovoltaic and a wind source. Furthermore, a lead-acid battery guarantees the stability of the DC bus while a hydrogen cell ensures the reliability of the system by avoiding blackout conditions and increasing interaction with the loads. The fuzzy rule bank, initially built using the expert’s knowledge, is optimized with the aforementioned procedure, maximizing external energy and minimizing consumption. The complete scheme, modeled using MatLab/Simulink, highlighted performance comparable to fuzzy Takagi–Sugeno systems optimized using a hybrid approach based on particle swarm optimization (to structure the antecedents of the rules) and minimum batch squares (to optimize the output).

Development of paraffin wax & used cooking oil based composite thermal energy storage for efficient potable water generation in a solar distillation unit

The purpose of this study is to develop a novel composite thermal energy storage system (CTESS) using blends of used cooking oil (UCO) and paraffin wax (PW) and experimentally investigate its effect on the performance of solar still for effective seawater desalination. The CTESS was developed by mixing UCO with PW in various volume ratios and the volume ratio of UCO and PW was optimized at 1:1. The objective was to examine the performance of the solar still with used cooking oil and paraffin wax (SSUCO) and compare it with a conventional solar still (CSS) without any energy storage. The investigation was carried out experimentally, and the results show that the SSUCO significantly enhanced freshwater production compared to CSS. On the first day, the overall freshwater production from SSUCO and CSS was found to be approximately 2870 ml/m2 and 1830 ml/m2, respectively, whereas, on the second day, it was about 2680 ml/m2 and 1750 ml/m2. The productivity of SSUCO increased by 56.83 % and 53.14 % on day 1 and day 2, respectively. The thermal efficiency of SSUCO on day 1 and day 2 was found to be 45.52 % and 41.67 %, respectively, whereas, for CSS, it was 29.03 % and 27.21 %. Economic analysis showed that the cost per litre of yield and payback period for SSUCO was reduced by 40.54 % compared to CSS. Moreover, the environmental analysis revealed that the carbon credit gained by SSUCO was 64.2 % higher than that of CSS. The results indicate that CTESS is a highly promising technique for seawater desalination in solar stills. It provides notable advantages such as increased productivity, enhanced thermal efficiency, and significant economic and environmental benefits.

Energy Management Optimization of Fuel Cell Hybrid Ship Based on Particle Swarm Optimization Algorithm

In order to optimize the energy management strategy and solve the problem of the power quality degradation of fuel cell hybrid electric ships, a particle swarm optimization algorithm based energy management strategy is proposed in this paper. Taking a fuel cell ship as the target ship, a system simulation model is built in Matlab/Simulink to verify the proposed energy management strategy. Through simulations and comparisons, the bus voltage curve of the optimized hybrid power system fluctuates more gently, and the voltage sag is smaller. The amplitude of the voltage fluctuation under maneuvering conditions is reduced by 55% compared with that of the original ship. The charging and discharging process of the composite energy storage system is optimized under maneuvering conditions, the power quality of the marine power grid is improved, and the use of the energy management strategy can extend the service life of the battery.

Adaptive rule control strategy for composite energy storage fuel cell vehicle based on vehicle operating state recognition

In order to fully exploit the advantages of each energy source, prolong the lifetime of the composite energy storage system, which is composed of a fuel cell, battery, and ultracapacitor, and reduce the comprehensive operating cost of the vehicle, by analyzing the influence on the vehicle's energy economy and energy source life at different power supply sequences of energy sources, an adaptive rule control strategy based on vehicle operation state recognition is proposed for the vehicle with the composite energy storage system. This strategy can automatically select the optimal energy source supply sequence according to the current vehicle speed and acceleration. The effectiveness and superiority of the strategy are verified by comparing it with the traditional rule strategy. Additionally, the key parameters of the proposed strategy, which have a large impact on the comprehensive operating cost of the vehicle, are recognized based on sensitivity analysis and optimized by a genetic algorithm. The simulation shows that the comprehensive operating cost of the vehicle under the WLTP drive cycle is reduced by 10.94% after optimization.

Hierarchical energy management strategy for fuel cell/ultracapacitor/battery hybrid vehicle with life balance control

Fuel cell (FC) is an ideal power source for electric vehicles with high efficiency and little pollution. However, with its weak dynamic reaction, it needs to be used in combination with other energy storage devices, and the coupling of multiple energy sources makes it difficult to fully utilize the system performance. Meanwhile, the cost and durability of FC hinder its commercialization. This paper takes the composite energy storage system composed of FC, battery (BAT) and ultracapacitor (UC) as the research object. In order to improve the system performance, a hierarchical energy management strategy is proposed based on the analysis of the relationship between UC output power and vehicle demand power under dynamic programming (DP) strategy, taking into account the vehicle energy consumption and energy source lifetime. A fuzzy control based on speed prediction and a dynamic state-of-charge (SOC) threshold control optimization algorithm of UC based on working condition recognition are designed to optimize the hierarchical control strategy. In the upper layer strategy, for realizing the online real-time distribution of UC output power, the generalized regression neural network is used to learn the relationship between UC output power and demand power under DP strategy; in the lower layer strategy, the power of the FC and BAT is distributed using an equivalent energy minimization strategy. Based on above strategy, this paper proposes a life balance control strategy for energy sources to maximize the lifetime of the composite energy storage system. Simulation and experimental results show that the proposed strategy has a comparable life-cycle average operating cost to the DP strategy with better life mileage.

Energy management and control for direct current microgrid with composite energy storage system using combined cuckoo search algorithm and neural network

This paper describes a novel energy management strategy (EMS) based on a combined cuckoo search algorithm and neural network (CCSNN) for the control of a DC microgrid (DCMG) with composite energy storage system (CESS). The presented control technique intends to enhance the power-sharing between batteries and supercapacitors (SCs) in order to handle the demand-generation discrepancy, preserve state-of-charge (SOC) inside predetermined parameters, and manage DC bus voltage (DBV). Furthermore, the efficacy of the suggested technique for enactment in terms of voltage overshoot and settling time was compared to conventional control strategy-based findings. The results are validated by experimental studies employing a hardware-in-loop (HIL) configuration on an FPGA-based real-time simulator.

Design and Performance Analysis of Super Highspeed Flywheel Rotor for Electric Vehicle

The optimal design of a super highspeed flywheel rotor could improve flywheel battery energy density. The improvement of flywheel battery energy density could enhance the performance of the flywheel lithium battery composite energy storage system. However, there are still many problems in the structure, material and flywheel winding of super highspeed flywheels. Therefore, in this paper, electric flywheel energy and power density parameters are designed based on CPE (Continuous Power Energy) function and vehicle dynamics. Then, according to the design index requirements, the structure, size and material of the electric flywheel rotor are designed. Furthermore, the numerical analysis model of stress and displacement of multi-ring interference fit flywheel rotor under plane stress state is established. On this basis, the influence laws of flywheel rotor wheel flange numbers and interlaminar interference on stress distribution of flywheel rotor are analyzed, and the assembly form of wheel flange is determined. Finally, the stress check of the flywheel rotor is completed. The results show that the super highspeed flywheel rotor designed in this paper meets vehicle dynamics requirements in terms of energy storage and power. In terms of strength, it meets the design requirements of static assembly stress and dynamic stress at maximum speed.

Model predictive control of solar photovoltaic‐based microgrid with composite energy storage

SummaryThe renewable energy (e.g., solar photovoltaic)‐based grid‐connected microgrid (MG) with composite energy storage system (CESS) is feasible to ensure sustainable and quality power to the commercial and domestic load demands. Effective control systems provide the dynamic performance of such deployed MGs. This paper investigates the application of the finite control‐set model predictive controller (FCS‐MPC) for solar photovoltaic‐based grid‐connected MGs with composite energy storage. FCS‐MPC considers the discrete nature of interfacing (DC–AC and DC–DC) converters into the control algorithm to predict the optimal control command for reference current tracking. Compared to classical control approaches, FCS‐MPC provides a fast‐dynamic response, discards the modulation stage, and effectively handles the effects of dynamic source and load variations and nonlinear loads. The control system encapsulates a proportional–integral (PI) controller, low‐pass filter (LPF), power management algorithm (PMA) unit, and followed by the FCS‐MPC approach. The CESS unit consists of a battery and supercapacitor storage system. The efficacy of the FCS‐MPC approach is verified through the MATLAB/Simulink results. Solar photovoltaic variation due to irradiance, utility grid availability, electricity pricing, and dynamic load variations are considered in the implementation. Furthermore, real‐time simulation of the proposed method is validated using OPAL‐RT OP4510 real‐time simulator.

Parameter Matching Methods for Li Battery–Supercapacitor Hybrid Energy Storage Systems in Electric Buses

The parameter matching of composite energy storage systems will affect the realization of control strategy. In this study, the effective energy and power utilizations of an energy storage source were defined. With the miniaturization of a composite energy storage system as the optimization goal, the linear programming simplex method was employed to obtain the optimized masses of Li batteries and supercapacitors under the constraints of maximum speed, climbing gradient, acceleration time and cost-effectiveness. As the module numbers shall be integers, the matching results were modified in combination with the graphical method. Owing to the influences of parameter matching schemes on the overall performance and battery life, the critical points of constraints were analyzed and the most appropriate matching numerical points of the composite energy storage system were identified. Simulation and experimental analysis were conducted under practical urban road conditions in China. The results show that the proposed matching method delivers accurate results. Compared with conventional electric buses, the mileage and overall performance of the prototype bus are improved.

Model of a Composite Energy Storage System for Urban Rail Trains

Model of a Composite Energy Storage System for Urban Rail Trains

Power Distribution Strategy for an Electric Bus with a Hybrid Energy Storage System

To address the power distribution problem that occurs in hybrid energy storage systems (HESSs) in electric vehicles, a fuzzy control distribution method is proposed in this paper, taking the vehicle demand power; supercapacitor power, PSC;; and lithium battery power, Pbat, as the inputs and the power distribution factor of the supercapacitor as the output to control the power distribution of the composite energy storage system, in addition to dividing the whole working condition into three time scales, namely, long, medium and short. In this study, we conducted a comprehensive analysis and comparison with typical control methods regarding the energy storage element output power, battery state of charge (SOC) change, energy flow diagram and power frequency. The simulation experiment results show that the proposed strategy is more effective in reducing the peak output power of the power battery, improving the effective power utilization rate of HESS and the effective energy utilization rate. In order to further verify the effectiveness of the control strategy, a pure electric bus power system test bench was built based on similar principles, and a representative time period under the driving conditions of the China city bus (CHTC-B) was selected, involving an acceleration process from 30 to 48 s (process 1), a uniform speed process from 636 to 671 s (process 2) and a regenerative braking process from 1290 to 1304 s (process 3), further verifying the effectiveness and feasibility of the proposed control strategy.

Control Optimization of Composite Energy Storage System Based on Particle Swarm Optimization

Control Optimization of Composite Energy Storage System Based on Particle Swarm Optimization

The FUZZY CONTROL STRATEGY OF URBAN RAIL ENERGY BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM

The city rail train starts and brakes frequently in the process of operation, and the existing braking technology can not make full use of this part of energy. In this study, a lithium battery super capacitor composite energy storage system is proposed, which uses the fuzzy control of particle swarm optimization algorithm for energy optimization management. The fuzzy energy controller is established to optimize the system parameters by using particle swarm optimization (PSO) algorithm. Simulation results show that the strategy can not only optimize the energy management of urban rail trains, but also improve the stability, reliability and economic performance of train operation and reduce fuel consumption.