Energy Storage Module Research Articles

Parametric investigation and optimization of phase change material-based thermal energy storage integrated desiccant coated energy exchanger through physics informed neural networks oriented deep learning approach

To improve the energy exchange abilities, and to enhance indoor air quality, a desiccant-coated energy exchanger (DCEE) is a capable substitute compared to conventional energy exchangers such as fixed beds and desiccant wheels. Thus, accurately predicting the DCEE's physical characteristics is crucial for enhancing the system's performance. Therefore, in the current study, a novel data-driven modeling methodology utilizing physics-informed neural networks (PINNs) is developed to predict the exit parameters of DCEE, like the outlet temperature of cooling water, the outlet temperature of the air, and the outlet-specific humidity of the air. The performance characteristics of DCEE are evaluated using PINN by considering different input parameters. The performance parameters selected for the DCEE performance assessment are dehumidification capacity, thermal coefficient of performance, and heat recovery efficiency. The coated desiccant material chosen for the present study is silica gel. Good agreement is obtained between the PINN and experimental results for both the steady-state and transient cases, proving the PINN method's capability in solving multiple physics-based partial differential equations (PDEs) on a single domain with a maximum discrepancy of ±7.8 %. The developed model is used to obtain the optimal inlet conditions for a given operating condition. Adsorption kinetics of the coated desiccant silica gel revealed that the maximum water uptake capability for the given operating range is 0.345 g.g−1. A case study has been carried out by integrating an industrial waste heat-driven DCEE with a thermal energy storage module (TES) to analyze the energy storage ability during regeneration. A parametric study has been conducted to examine the transfer characteristics of the TES module. Further, the effectiveness of the TES module for five different phase change materials (PCMs) has been assessed. Finally, the seasonal energy efficacy ratio (SEER) of five different PCMs was investigated for 365 days to evaluate year-round performance. The effectiveness of thermal energy storage is maximum for Palmitic acid and minimum for Climsel C48, with corresponding values of 0.73 and 0.37. SEER is the largest for Palmitic acid and lowest for Climsel C48. The values of SEER for Palmitic acid during the summer and winter seasons are 5.489 and 3.31, whereas the values of SEER for Climsel C48 during the summer and winter seasons are 5 and 2.89, respectively.

Operating characteristics analysis and capacity configuration optimization of wind-solar-hydrogen hybrid multi-energy complementary system

Wind and solar energy are the important renewable energy sources, while their inherent natures of random and intermittent also exert negative effect on the electrical grid connection. As one of multiple energy complementary route by adopting the electrolysis technology, the wind-solar-hydrogen hybrid system contributes to improving green power utilization and reducing its fluctuation. Therefore, the moving average method and the hybrid energy storage module are proposed, which can smooth the wind-solar power generation and enhance the system energy management. Moreover, the optimization of system capacity configuration and the sensitive analysis are implemented by the MATLAB program platform. The results indicate that the 10-min grid-connected volatility is reduced by 38.7% based on the smoothing strategy, and the internal investment return rate can reach 13.67% when the electricity price is 0.04 $/kWh. In addition, the annual coordinated power and cycle proportion of the hybrid energy storage module are 80.5% and 90%, respectively. The developed hybrid energy storage module can well meet the annual coordination requirements, and has lower levelized cost of electricity. This method provides reasonable reference for designing and optimizing the wind-solar-hydrogen complementary system.

A multidirectional pendulum kinetic energy harvester system for low-power appliances in new energy buses

Wireless sensors play a crucial role in vehicle operations. The effective energy harvesting for self-powering these sensors has emerged as a critical area of interest in recent years. This paper presents a multidirectional pendulum kinetic energy harvester system (MP-KEHS) designed to power low-power sensors in vehicles. The MP-KEHS consists of four main components: an energy capture module, a motion transfer module, an energy conversion module, and an electric energy storage module. The energy capture module, comprising a mass ball and a turntable, captures omnidirectional inertial kinetic energy during vehicle acceleration, deceleration, and turning. In the motion transfer module, a one-way gear module converts the multidirectional rotations of the energy capture module into unidirectional rotations, while the planetary gear train enables speed coupling during simultaneous vehicle acceleration and turning. The energy conversion module utilizes a generator to transform rotational kinetic energy into electric energy. The electric energy storage module stores the electric energy in a supercapacitor after passing through a voltage regulator circuit, providing power to low-power devices. Using of multi-body dynamics software and Simulink, the swing angle of the mass ball was determined under four real driving cycles. Experimental results demonstrated that the average output power of the MP-KEHS reached 116.8 mW. Charging the capacitors of 220 μF, 470 μF, and 1000 μF from 0 V to 1 V takes 8 s, 24 s, and 93 s, respectively. Finally, the MP-KEHS was applied to a bus on the Liaocheng University campus, achieving an average output power of approximately 176 mW, which satisfied the power requirements of the sensors. These findings indicate that the MP-KEHS effectively harnesses the vehicle's otherwise wasted inertial energy, enabling wireless sensor self-powering.

An Inertial Energy Harvester Based on Noncontact Magnetic Force for Self‐Powered Applications in New Energy Buses

The advent of energy‐efficient, next‐generation driverless buses places substantial reliance on an array of wireless sensors. In response to this challenge, converting and utilizing these buses' local inertial kinetic energy emerges as a practical strategy for achieving self‐powered capabilities for low‐power appliances. Herein, an inertial energy harvester based on noncontact magnetic force for self‐powered applications in new energy buses is introduced. The harvester system comprises energy capture, mechanical amplification, conversion, and storage modules. The energy capture module proficiently captures and converts the otherwise wasted inertial kinetic energy into magnetic force. The magnified magnetic force produced by the mechanical amplification module efficiently transforms into electrical power within the energy conversion module. Afterward, the alternating current is regulated and stored within the supercapacitor by the energy storage module, achieving self‐powered capabilities for low‐power vehicle appliances. At the same time, combined with the bench test, the maximum output power of the harvester under different vehicle acceleration scenarios is obtained. Taking the campus bus of Liaocheng University as the application object, the average output power of the harvester in the actual operation of the campus is 23.71 mW, which can effectively promote the realization of wireless sensor self‐powered technology in new energy vehicles.

AC-DC-DC Converter for Small Power Energy Storage Systems

The energy transformation driven by the development of renewable energy sources has become a reality for all power grid users. Prosumer energy, primarily utilizing photovoltaic installations, is one of the fastest-growing market segments. The advancement of technology, a decrease in electrochemical energy storage prices, and changes in the legal framework governing energy billing for grid-fed power have led to a growing interest in expanding prosumer installations with energy storage modules. This article presents the authors’ concept and expected functionalities of a prosumer system equipped with energy storage based on theoretical assumptions, simulation analyses, and experimental research. Additionally, it covers the design and functionality of a hybrid converter; its experimental validation, including an analysis of operational modes; the development of a control algorithm under real conditions; and the efficiency testing of the device.

Self-supportive Pd0.2Ni58Fe30O11.8 nanowires for solar-driven self-powered water/seawater splitting with large current density

Solar-driven water/seawater splitting system is a significant renewable technology for obtaining hydrogen fuel, while the drawbacks of sunlight with intermittent and unstable limit their widespread practical applications. It is an efficient and renewable way to add an energy storage module between the photovoltaic system and electrolyzer to operate a self-powered and uninterrupted electrolyzer for improving the development of solar-driven water/seawater splitting. Herein, we develop an efficient and stable trifunctional electrocatalyst of self-supportive Pd0.2Ni58Fe30O11.8 nanowires for Zn-air batteries and overall seawater splitting, which connect with photovoltaic cells to assemble solar-driven self-powered electrocatalytic water splitting system. It is noticed that the obtained self-supportive Pd0.2Ni58Fe30O11.8 nanowires show a special 3D network structure connected by nanowires with a hierarchical structure, improving the charge and mass transfer on their surface. Furthermore, the self-supportive Pd0.2Ni58Fe30O11.8 nanowires displayed low overpotentials of 77 and 233 mV to deliver current densities of 100 mA cm−2 for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) processes, which is at the top level of great prospects for industrialization. A highly efficient and stable 24-hour integral water exchange system was successfully established with a circuit output voltage of 1.88 V and constant and stable current density throughout the system. The solar-powered uninterrupted overall water-splitting systems open up exciting opportunities for fully renewable and sustainable energy applications.

Statistical analysis and Monte-Carlo simulation of printed supercapacitors for energy storage systems

This study presents a comprehensive statistical analysis of experimental parameters for 12 printed supercapacitors (SCs) using previously proposed equivalent circuit models (ECMs). Statistical distributions and descriptive statistics, including mean, P-value, and standard deviation (std), are reported indicating a normal distribution for various SC parameters. A statistical method is introduced to determine the maximum potential std in capacitance of multiple SCs within an energy storage module, ensuring voltage limits are not exceeded. A linear relationship is discovered between the applied voltage on the module comprising three SCs in series and the maximum potential std of capacitance, ensuring safe operation. Additionally, a statistical method predicts the energy window range of the SC module after operating an IC chip, enabling better decision-making and system management. Monte-Carlo (MC) simulations predict the long-term charge and discharge performance of individual SCs and the series-connected modules. Results indicate that as long as the parameters’ std remains below a defined threshold, charging behavior remains consistent. The MC simulations provide insight into voltage window ranges after 31 days of self-discharge, aiding in performance prediction and risk assessment. The statistical study approach empowers researchers in the field of printed SC energy storage, supporting performance evaluation, design validation, and evidence-based decision-making.

Self-switching circuit of TENG for energy storage and power management in harvesting wind energy

As an important green energy in our life, natural wind energy is widely used in power generation. Triboelectric nanogenerator (TENG) can convert wind energy in the environment into electrical signal. In this study, two independent TENGs in parallel (FHS-TENG) and the power management circuit composed of passive self-switching circuit and LC filter circuit constitute a self-supplying system, which is committed to harvesting wind energy in the environment and outputting stable voltage and improving energy storage performance. The self-switching circuit mainly includes rectifier module, energy storage module, the self-switching module, and filter module. And the on/off state of the passive self-switching is mainly controlled by two transistors, which implements the effect of switch. The results demonstrate that the energy stored by the power management circuit is more than 100 times higher than that of the universal circuit at 100 μF capacitor, and the calculator is in stable working order in simulated wind conditions. This work provides a new strategy for the passive electronic switch of TENG and the improvement of circuit energy storage performance, which is meaningful for the further application and industrialization of TENG.

Experimental Study on the Effect of State of Charge on Failure Propagation Characteristics within Battery Modules

To investigate the effect of different states of charge(SOC) on the thermal runaway(TR) propagation behaviors within lithium-ion-batteries based energy storage modules, an experimental setup was developed to conduct failure propagation tests on battery modules at an SOC of 97%, 85%, and 50%. The result indicates that an increase in the SOC of batteries can decrease the TR trigger temperature, making batteries trigger TR earlier and reducing the average failure propagation time between two adjacent cells. In addition, the failure propagation tests reveal that at higher SOCs, the TR reaction becomes more violent, the maximal reaction temperature is also much higher, and the damage to the battery module is severe. Compared to the battery module with 97% SOC, the TR trigger time of the battery module with 50% SOC was postponed by approximately 57.8%. Meanwhile, the average failure propagation time got prolonged by approximately 36.0%. Thus, this study can provide references for the thermal safety design of energy-storage battery modules.

Model Development and Optimization of a Solid Oxide Fuel Cell/Gas Turbine Hybrid Power System for Electric Aviation

With countless global industries pledging and pursuing decarbonization targets set for the 2030 – 2050 timeframe, the aerospace industry faces many key challenges including reduction of greenhouse gas emissions, contrail abatement, and development/adoption of technologies with higher Fuel-to-Electricity (FTE) conversion efficiencies. One such technology identified as a potential fit for commercial aircraft is the solid oxide fuel cell and gas turbine (SOFC-GT) hybrid power system. Progress in system-level SOFC-GT modeling is critical to produce higher fidelity feasibility studies used to influence SOFC design and performance targets of the future. In this study, the first ProMax 5.0-based SOFC-GT model was developed, validated, and optimized. The impact of process configuration, balance-of-plant, and operating conditions were investigated. An optimal process design comprising 8 SOFC stacks and 7 Energy Storage and Power Generation (ESPG) modules with a total power output of > 7.0-MW and FTE conversion efficiencies of 73 – 76% is reported. Additionally, preliminary airplane architecture with the 7 onboard ESPG modules is presented to show the feasibility of future, hybrid electric airplane design.

Advances in Two-dimensional (2D) Inorganic Chiral Materials and 2D Organic-inorganic Hybrid Chiral Materials

Abstract: Recently, two-dimensional (2D) materials have gained immense attention, as they are promising in various application fields, such as energy storage, thermal management, photodetectors, catalysis, field-effect transistors, and photovoltaic modules. These merits of 2D materials are attributed to their unique structure and properties. Chirality is an intrinsic property of a substance, which means the substance can not overlap with its mirror image. Significant progress has been made in chiral science, for chirality uniquely influences a chiral substance's performance. With the rapid development of chiral science, it became unveiled that chirality not only exists in chiral organic molecules but can also be induced in 2D inorganic materials and 2D organic-inorganic hybrid materials by breaking the chiral symmetry within their framework to form 2D chiral materials. Compared with 2D materials that do not have chirality, these 2D inorganic chiral materials and 2D organic-inorganic hybrid chiral materials exhibit innovative performance due to chiral symmetry breaking. Nevertheless, at present, only a fraction of work is available which comprehensively sums up the progress of these promising 2D chiral materials. Thus, given their high potential, it is urgent to summarize these newly developed 2D chiral materials comprehensively. In the current study, to feature and highlight their major significance, the recent progress of 2D inorganic materials and 2D organic-inorganic hybrid materials from their chemical composition and categories, application potential associated with their unique properties, and present synthesis strategies to fabricate them along with discussion concerning the development challenges and their bright future were reviewed. This review is anticipated to be instructive and provide a high understanding of advanced functional 2D materials with chirality.

Conjugate Mathematical Model of Heat and Mass Transfer in the Thermal Energy Storage Module with a “Solid Body–Liquid” Phase Transition

Conjugate Mathematical Model of Heat and Mass Transfer in the Thermal Energy Storage Module with a “Solid Body–Liquid” Phase Transition

Integrated Control Strategy of Voltage and Frequency Modulation for the Photovoltaic-storage Unit

With the increasing installation of new energy power generation, photovoltaic power generation has become a significant component of the power system. However, the random and fluctuating nature of photovoltaic power generation can pose a challenge. The combination of photovoltaic power generation with energy storage using a photovoltaic-storage unit integrated machine can help mitigate the fluctuations of photovoltaic power generation output and improve the power quality of photovoltaic grid connection. In this paper, we propose a grid-connected integrated control strategy for the photovoltaic-storage unit integrated machine. We use a hybrid energy storage module with a lithium battery and a super capacitor as the energy storage unit for the photovoltaic-storage unit integrated machine. Finally, we use the MATLAB/Simulink simulation platform to simulate and verify the effectiveness of our proposed strategy.

Dynamic simulation of a triple-mode multi-generation system assisted by heat recovery and solar energy storage modules: Techno-economic optimization using machine learning approaches

Intelligent design and operation optimization allow energy systems to take advantage of the flexibility that multi-generation provides. This study proposes a basic solar-driven system integrated with thermal energy storage for round-the-clock energy harvesting. A modified configuration is then designed incorporating innovative multi-heat recovery approaches to increase the capacity and product diversity of the basic system. The modified system is able to cover vital urban utilities such as electricity, fresh water, cooling, and hydrogen throughout the day. To overcome the time-consuming procedure of dynamic techno-economic simulation as well as the limitation of commercial engineering equation solvers for tri-objective optimization, a deep learning approach is developed to reduce the computational complexity and improve the analysis accuracy. In this regard, the trained neural networks play an intermediary role in coupling the developed code with the MATLAB optimization toolbox. A comparison between the modified and conventional configurations indicates that implementing the multi-heat recovery approach results in a 29% increase in power generation while only increasing the overall system cost by 1.97%. From an economic perspective, the Sankey diagram depicts that the storage unit with a cost rate of 12.25 $/h accounts for 6.77% of the plant's cost rate, which enables the system to operate continuously. According to the sensitivity analysis and contour plots, the number of collectors significantly affects the total cost rate and fresh water production capacity while it has no tangible effect on the exergy efficiency.

High-performance hybrid nanogenerator for self-powered wireless multi-sensing microsystems

Wireless sensor network nodes are widely used in wearable devices, consumer electronics, and industrial electronics and are a crucial component of the Internet of Things (IoT). Recently, advanced power technology with sustainable energy supply and pollution-free characteristics has become a popular research focus. Herein, to realize an unattended and reliable power supply unit suitable for distributed IoT systems, we develop a high-performance triboelectric-electromagnetic hybrid nanogenerator (TEHNG) to harvest mechanical energy. The TEHNG achieves a high load power of 21.8 mW by implementing improvements of material optimization, configuration optimization and pyramid microstructure design. To realize a self-powered integrated microsystem, a power management module, energy storage module, sensing signal processing module, and microcontroller unit are integrated into the TEHNG. Furthermore, an all-in-one wireless multisensing microsystem comprising the TEHNG, the abovementioned integrated functional circuit and three sensors (temperature, pressure, and ultraviolet) is built. The milliwatt microsystem operates continuously with the TEHNG as the only power supply, achieving self-powered operations of sensing environmental variables and transmitting wireless data to a terminal in real time. This shows tremendous application potential in the IoT field.

Study on effective front region thickness of PCM in thermal energy storage using a novel semi-theoretical model

Thermal energy storage in mobile applications, particularly battery of electric vehicles, is currently gaining a lot of importance. In this paper, a semi-theoretical time-dependent mathematical model of the phase change in a double shell thermal energy storage module has been developed where the inner tube is a heat exchange surface. An effective front region thickness for the melting and solidification process has been studied. The proposed model is calibrated based on our experimental data. The purpose of such a model is to enable the optimization of the geometry of the energy storage modules in terms of the PCM to the TES container mass ratio and enhancement of phase change rate. In addition, results obtained for a single tube can be used in the bundle of tubes in shell and tube TES design. The results have shown that for the larger diameter of the module (smaller difference between the working tube and shell diameter) the optimal working time is around 2000 s.

A negative-work knee energy harvester based on homo-phase transfer for wearable monitoring devices

Wearable health monitoring devices can effectively capture human body information and are widely used in health monitoring, but battery life is an important bottleneck in its development. A full negative-work energy harvester based on the homo-phase transfer mechanism by analyzing human motion characteristics was proposed in this paper. The system was designed based on the homo-phase transfer mechanism, including a motion input module, gear acceleration module, energy conversion module, and electric energy storage module. The output performance in three human-level, downhill, and running states was tested, respectively. Finally, we have evaluated the feasibility of an energy harvester powering wearable health monitoring devices, and the harvester can generate 17.40 J/day power, which can satisfy the normal operation of a typical health monitoring device. This study has certain promoting significance for the development of a new generation of human health monitoring.

MAXIMIZATION THE LATENT HEAT STORAGE UNIT (LHSU) ENERGY SAVING USING SIMULATED ANNEALING ALGORITHM

An integration between latent heat storage unit (LHSU) and an air cooler was studied to reduce the space cooling energy consumption in telecommunications base stations (TBSS). A mathematical model was developed to address the heat transfer processes within energy storage modules and air cooler. Furthermore, a solid works simulation was used to simulate the real system virtually. A simulated annealing algorithm (SA) was utilized to maximize annual energy savings ratio which was considered a performance criterion for the proposed system. The calculations included comparisons the relative errors of air and temperature difference between the optimized using simulated annealing algorithm and tested (virtual) results which were calculated for both operation modes energy charging and energy discharging. The obtained results illustrated a remarkable improvement both relative errors and annual energy savings ratio for the study case.

Triple-mode hybridized generator for efficient water flow energy harvesting and water quality monitoring applications

Water quality monitoring is essential for river ecological environment. Harvesting water flow energy for river environmental monitoring is a promising solution for self-powered sensing technology. In this work, based on the triboelectric–electromagnetic (TENG-EMG) working principle, a comprehensive strategy appropriately hybridizes the solid-solid TENG (SS-TENG), solid-liquid TENG (SL-TENG) and EMG based on water wheel structure for harvesting water flow energy. The triple-mode hybridized generator (TMHG) in a limited space is combined effectively through ingenious structural design, which greatly improves the space utilization. An introduction of the combination of TMHG and buoy structure provides stable operating conditions for power supply. The basic TMHG in terms of structural parameters, response characteristics, power supply capacity and sensing characteristics is systematically discussed. Specially, after optimizing the structural parameters, the SS-TENG, SL-TENG and EMG deliver an instantaneous power of 1.44, 0.15 and 15.9 mW, and 480, 120 and 122 LEDs array can be simultaneously illuminated at the rotate speed of 90 rpm, respectively. The output of SL-TENG has strong correlation with flowing velocity and water PH, further demonstrating a potential application of TMHG on self-driven sensing of river state. A triple-channel hybridized power management (TcHPM) strategy consisting of energy collection module, storage module and mechanical switch is developed to co-manage the electrical outputs of three generating modules in TMHG. Furthermore, a wireless self-powered monitoring system using TMHG as power supply is further developed and demonstrated for water quality monitoring in terms of water temperature and total dissolved solids. This paper not only provides a potential strategy towards effective water flow energy harvesting, but also demonstrates the potential applications of the TMHG in water quality monitoring.

Structure design and analysis of upper limb wearable passive power-assisted exoskeleton robot

The upper limb exoskeleton robot has been a key research direction at home and abroad in recent years. Still, the existing upper limb exoskeleton robot has poor coupling with the human body, and the power assistance effect could be better. In this paper, the strength of each muscle group of the upper limb when the human body is carrying objects is measured as reflected by the surface EMG signal of the human body, and the human kinematics is analyzed to guide the design of the passive exoskeleton robot of the upper limb. First, the spring tension and compression system model is established for the upper limb of the human body. The model is statically analyzed, the forces and moments on each joint are calculated, and each muscle’s actual output data when carrying objects is estimated. Based on the muscle kinematics model, a passive upper limb exoskeleton robot is designed. The robot is divided into three modules, namely, the arm module, shoulder module, and back module, using ergonomics and modular design ideas. The energy storage module and joint degree of freedom of the exoskeleton are analyzed to ensure that the exoskeleton meets the requirements of ergonomics, and the key components are checked and simulated. The results show that the designed upper limb wearable passive power-assisted exoskeleton robot meets the strength requirements, which verifies the rationality of the structure design.