Performance Of Storage System Research Articles

Energy storage, thermal-hydraulic, and thermodynamic characteristics of a latent thermal energy storage system with 180-degree bifurcated fractal fins

The low thermal conductivity of organic phase change materials limits the performance of latent thermal energy storage (TES) systems. Inspired by fractal theory, this study proposes an innovative 180° fractal fin for enhancing the thermal performance of latent TES systems. The effects of length ratios (l) and fractal levels (N) are numerically investigated employing the enthalpy-porosity method. Compared with traditional rectangular fins, the results indicate that the 180° fractal fins reduce the integral average value of the maximum velocity by 2.24%–48.51%, which indicates the suppression of natural convection by the latter. Increasing l and N result in a general increase in melting time. Compared to the TES systems without fins and with rectangular fins, the 180° fractal fins can respectively reduce melting time by up to 88.79% and 28.00%, increase integral average Nusselt number by up to 7.30 times and 34.21%, and enhance energy storage power by a maximum of 8.55 times and 38.71%. Moreover, flow viscous entropy generation can be neglected compared to thermal entropy generation. In contrast to rectangular fins, the employment of fractal fins leads to a maximum reduction of 90.06% and 99.10% in total frictional entropy generation and thermal entropy generation, respectively.

Heat transfer enhancement of nanofluids in concentric cylindrical heat exchanger

Two models of heat transfer channels for concentric cylindrical heat exchangers with porous ribs are developed herein to optimize the transfer efficiency of the heat storage reactor channels. Rings and spiral ribs are added to the smooth circular tube inside the reactor. Spoiler holes are arranged in the ribs to reduce the stagnation area around the ribs. The effects of coolant (SiO2–H2O nanofluids), rib shapes, and the number of holes in the rib on the overall performance of the heat storage system were numerically investigated. Results revealed that the 0.5% mass fraction nanofluids are the most suitable working fluid for channel thermal transport in the simulated Reynolds number range. Both ring ribs and spiral ribs reinforce the heat exchange of the pipe to varying degrees. Spiral perforated ribs have superior heat transfer and drag reduction performance compared with ring ribs. The comprehensive performances of spiral ribs are always higher than those of ring ribs under all conditions.

Principles and Design of Biphasic Self‐Stratifying Batteries Toward Next‐Generation Energy Storage

AbstractLarge‐scale energy storage devices play pivotal roles in effectively harvesting and utilizing green renewable energies (such as solar and wind energy) with capricious nature. Biphasic self‐stratifying batteries (BSBs) have emerged as a promising alternative for grid energy storage owing to their membraneless architecture and innovative battery design philosophy, which holds promise for enhancing the overall performance of the energy storage system and reducing operation and maintenance costs. This minireview aims to provide a timely review of such emerging energy storage technology, including its fundamental design principles, existing categories, and prototype architectures. The challenges and opportunities of this undergoing research topic will also be systematically highlighted and discussed to provide guidance for the subsequent R&D of superior BSBs while conducive to bridging the gap for their future practical application.

Principles and Design of Biphasic Self-Stratifying Batteries Toward Next-Generation Energy Storage.

Large-scale energy storage devices play pivotal roles in effectively harvesting and utilizing green renewable energies (such as solar and wind energy) with capricious nature. Biphasic self-stratifying batteries (BSBs) have emerged as a promising alternative for grid energy storage owing to their membraneless architecture and innovative battery design philosophy, which holds promise for enhancing the overall performance of the energy storage system and reducing operation and maintenance costs. This minireview aims to provide a timely review of such emerging energy storage technology, including its fundamental design principles, existing categories, and prototype architectures. The challenges and opportunities of this undergoing research topic will also be systematically highlighted and discussed to provide guidance for the subsequent R&D of superior BSBs while conducive to bridging the gap for their future practical application.

Design of reactive particle fluidized bed heat exchangers for gas–solid thermochemical energy storage

Concentrated solar power (CSP) systems integrated with a supercritical carbon dioxide (sCO2) Brayton power cycle are regarded as the primary future direction for CSP technologies. Calcium-based particles can be a suitable storage medium to achieve high temperatures exceeding 750 ℃. However, there have been few studies on reactive particle/sCO2 heat exchangers (HXs) to drive high-performance power cycles with high energy storage efficiencies. In this paper, the mechanisms by which chemically reactive particles release energy in a fluidized bed (FB) heat exchanger has been investigated to evaluate the performance of thermochemical storage systems. A 1-MWt thermal duty fluidized bed heat exchanger with sCO2 as the working fluid operating at 988 K was designed in different configurations, featuring single stage and multistage counter-flow HXs. A detailed shell and tube model combining the chemical reaction kinetics and the heat transfer between the fluidized particle and sCO2 FB HX design was developed. A comparison of sensible and chemical heat materials shows that thermochemical energy storage is advantageous due to the relatively short tube length and slow particle mass flow rate. The tube length and particle mass flow rate are reduced by 3.5 and 11.5 times, respectively. The average chemical conversion is 97.30 % for a one-stage heat exchanger, which is lower than the 99.95 % conversion achieved by the two-stage heat exchanger. Additionally, a sensitivity analysis was carried out to understand the impacts of key operating parameters on the process performance. These findings provide insights into the operational stability and efficiency of the system, contributing to the development of advanced heat exchangers for thermochemical energy storage applications.

Lithium‐free Redox Flow Batteries: Challenges and Future Prospective for Safe and Efficient Energy Storage

Considering the costs, waste, and impact on the environment of current energy consumption, accurate, cost‐effective, and safely deployed energy storage systems are required. Lithium‐free redox flow batteries (RFBs) are a feasible solution. RFBs can store enormous amounts of energy effectively and are increasingly used for large‐scale applications. The use of RFBs has significantly enhanced the performance of energy storage systems and effectively reduced the costs and wastage of energy storage operations. Vanadium‐based RFBs are an emerging energy‐storage technology being explored for large‐scale deployment owing to their numerous benefits, including zero cross‐contamination, scalability, flexibility, extended life cycle, and nontoxic working state. This study describes the fundamental operating principles of redox flow battery‐based systems as well as the design considerations and constraints placed on each component. It discusses recent progress in the design and deployment of RFBs for energy‐related applications and the remaining obstacles and prospects. Finally, this study highlights the enormous potential of RFBs and suggests some solutions to scale up the use of RFBs in the near future.

Influences of the number and length of longitudinal fins on the single and cyclic charging and discharging performance of vertical double-tube latent heat storage systems

Using longitudinal fins is one of the efficient ways to enhance the heat transfer performance in phase change materials (PCM) based latent heat thermal energy storage systems. However, the previous studies do not consider the influence of the fins' geometric parameters on the single and cyclic charging and discharging performance and thermal effectiveness of latent heat storage systems. This paper, thus, aims to fill the research gap by developing a three-dimensional numerical model to study the effects of the fin number (i.e., 2, 4, 6, and 8) and fin length (i.e., 11.25, 17.00, and 22.00 mm) on the PCM melting/solidification characteristics and evaluate the performance and thermal effectiveness of the vertical double-tube latent heat storage system using the enthalpy-porosity method. Paraffin wax (RT-55) is used as the PCM, and water is the heat transfer fluid. The results show that increasing the fin number to eight reduces the melting, solidification, and total cycle time by 58.0%, 61.4%, and 59.8%, respectively, while the number of daily complete melting and solidification cycles increases by 150.0%, compared with the base case (i.e., without fins). The eight-fin storage system increases the daily charging capacity, thermal energy storage, thermal energy storage rate, and average effectiveness during melting by 146.0%, 133.8%, 123.5%, and 109.0%, respectively; while during solidification, the discharging rate, the daily discharging capacity, and average effectiveness increase by 159.9%, 149.3%, and 176.2%, respectively, compared with the base case. Increasing the fin length to 22.00 mm reduces the melting, solidification, and total cycle time by 80.3%, 81.3%, and 80.8%, respectively, while the number of daily complete melting and solidification cycles increases by 418.0%, compared with the base case. The highest fin length increases the daily charging capacity, thermal energy storage, thermal energy storage rate, and average effectiveness during melting by 370.0%, 350.0%, 330.0%, and 210.0%, respectively; during solidification, the discharging rate, the daily discharging capacity, and the average effectiveness increase by 420.0%, 410.0%, and 470.0%, respectively, compared with the base case.

A Hybrid-salt Strategy for Modulating the Li+ Solvation Sheathes and Constructing Robust SEI in Non-flammable Electrolyte Lithium Metal Batteries.

The electrode interface determines the performance of an electrochemical energy storage system. Using traditional electrolyte organic additives and high-concentration electrolyte emerging recently are two generally strategies for improving the electrode interface. Here, a hybrid-salt electrolyte strategy is proposed for constructing the stable electrode interface. Through the solubilization effect of phosphate ester on LiNO3, a hybrid-salts-based non-flammable phosphate ester electrolyte system (HSPE) with LiPF6 and LiNO3 as Li salts has been developed. By the strong interaction between NO3- and Li+, the Li+ solvation sheath and solvent behaviors have been modulated, thus the undesirable effects of phosphate ester are eliminated and a robust SEI is formed. Experimental results and theoretical calculations illustrate that NO3- as a kind of strongly coordinating anion is able to reduce the number of TEP molecules and lower the reduction reactivity of TEP. The reconfigured Li+ solvation structure allows the formation of an inorganic-rich SEI on the electrode surface. As a result, in the designed HSPE, the average coulombic efficiency of lithium plating/stripping is increased to 99.12%. This work explored a new approach to construct the electrode interface and addressing the poor interface performance issue of phosphate esters.

Heat activated VO2 (R) cathodes for high-performance aqueous zinc ion batteries

We introduce a novel approach for design and production of vanadium dioxide (VO2) cathodes activated by heat, specifically tailored for use in aqueous zinc-ion batteries (ZIBs). Our cathodes exhibit distinctive metal-insulator transition (MIT) characterized by the shift between monoclinic (M) and tetragonal rutile (R) phases. The employment of an aqueous electrolyte in ZIBs enables successful operation of VO2 cathodes, showcasing phase transition and enhanced electrochemical performance above a readily attainable temperature of approximately 68 °C. The MIT feature enhances the charge transfer properties at electrode-electrolyte interfaces, resulting in notable improvements in specific capacity and energy densities. Fabricated VO2(M) cathodes underwent heat-triggered transformation to VO2(R), resulting in a remarkable increase (400 %) in capacity. At 0.1 A g−1, VO2(R) cathodes show specific capacity of 354.6 mAh g−1, yielding an impressive energy density of 461.0 Wh kg−1 for aqueous ZIBs. This exceptional performance can be attributed to abrupt change in electrical conductivity upon thermal activation of MIT. This work underscores pivotal role of thermally activated MIT in finely tuning electrochemical performance of energy storage systems, prospecting a promising avenue for further advancements.

Numerical simulation of a combined thermochemical-latent energy storage system based on paired metal hydrides and phase change material

The main goal of this paper is to assess the operating performance of a thermal energy storage system that combines latent and thermochemical heat storage for their utilization in industrial waste heat recovery as well as in solar power plants. Thermal energy is stored and released through endothermic desorption and exothermic absorption processes, thereby cycling hydrogen between two paired metal hydrides (MHs). The thermal performance of the dynamically coupled Mg2Fe/LaNi5 pair, which has never been investigated before, is presented in this study. Sodium acetate trihydrate is used as a PCM for the LaNi5-tank thermal management. Moreover, during the heat charging stage, the Mg2Fe-tank was subjected to a typical solar heat flux. A mathematical model has been established and utilized to simulate how the storage system would operate in practical situations. The impacts of the operating conditions, which are the efficiency of the supplied heat system, the HTF temperature, the heat transfer coefficient, and the initial temperature of the MH beds, on the storage system's performance are studied and discussed in detail. The findings from this investigation revealed that the pairing of Mg2Fe with LaNi5 at suitable operating conditions enabled the storage system to achieve a specific energy storage capacity of 2 MJ/kg of Mg2Fe and an efficiency of 87.1 %. The results of this study reveal the excellent performance of a potential and viable metal hydride pair (Mg2Fe/LaNi5) for its usage in thermal energy storage systems.

Multi-objective prediction and optimization of performance of three-layer latent heat storage unit based on intermittent charging and discharging strategies

An intermittent heat charging and discharging strategy is proposed for on-demand thermal utilization in a three-layer latent heat storage unit filled with nanoparticle-enhanced phase change materials. To optimize the utilization ratio of phase change materials, and the stored and released thermal exergy amounts, a multi-objective prediction and optimization methodology combining orthogonal experimental design, range and variance analyses, multi-nonlinear regression models, and non-dominated sorting genetic algorithm-II is introduced while considering the variables of nanoparticle concentration, heat transfer fluid velocity, and intermittent time interval. Results show that the time interval presents the most significant influence. Multi-nonlinear regression models for the above three variables are established with determination factors of 0.9871, 0.9625, and 0.9253, respectively. The ultimate optimal results are 0.8, 57094.03 J, and 43066.73 J, achieved at the three variables of 44.37 min, 0.38 m s−1 and 8.99%, respectively. The maximum verification error of 5.11% indicates the reliability of this methodology. The methodology aims to enhance the overall performance of the three-layer latent heat storage system by mitigating the constraints associated with single-performance optimization.

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.

Improvement of the performance of thermal energy storage systems with conical annular enclosure using magnetic field

This study numerically investigates the integration of passive and active heat transfer enhancement techniques to develop a highly efficient thermal storage system for quick charging rates. A conical design for the shell of latent heat thermal energy storage systems is combined with a diametrically magnetized cylindrical magnet to improve its performance. Numerical simulations explore the effect of the non-uniform magnetic field on latent heat thermal energy storage systems with conical enclosures at different tilting angles. The obtained results indicate that increasing the tilting angle of the enclosure of the nanoparticle enhanced phase change material reduces charging time by promoting more effective natural convection. Besides, the magnetic field enhances convective heat transfer between the heat transfer fluid and the nanoparticle enhanced phase change material, resulting in faster melting and the combined effects of magnetic and buoyancy forces reduce the overall melting time. The higher magnetic field intensities lead to a larger portion of the volume melting of nanoparticle enhanced phase change material and accelerated melting front advancement. Furthermore, the effect of the tilting angle on the process of melting is nearly eliminated for higher intensities of the applied magnetic field. This innovative combination holds significant potential for enhancing the performance of latent heat thermal energy storage systems, enabling efficient thermal storage and achieving rapid charging rates.

Bus Voltage Stabilization of a Sustainable Photovoltaic-Fed DC Microgrid with Hybrid Energy Storage Systems

Renewable energy sources play a great role in the sustainability of natural resources and a healthy environment. Among these, solar photovoltaic (PV) systems are becoming more economically viable. However, as the utility of solar energy conversion systems is limited by the availability of sunlight, they need to be integrated with electrical energy storage systems to be more sustainable. This paper aims to improve the control performance of a hybrid energy storage system (HESS) with PV power generation as the primary power source. HESSs stabilize DC microgrid systems by compensating for demand generation mismatches. Batteries and supercapacitors are chosen as energy storage elements; batteries have a high energy density and are capable of supplying and absorbing energy over a long duration, while supercapacitors can store and deliver energy very quickly. To enhance the stability of the system, each storage element is connected to the DC bus using a bidirectional Ćuk converter, which offers high efficiency, a continuous current, and minimal switching losses. This study proposes a proportional–integral (PI) controller combined with the fast nonsingular integral terminal sliding mode control (FNITSMC) for HESSs to adjust the power balance in a DC microgrid. FNITSMC has the advantage of enhancing the system states to reach the equilibrium point of a long sliding surface with a fast convergence rate. The reference current for FNITSMC is obtained using a PI controller combined with a low-pass filter (LPF), which eliminates the peaking current spikes on the battery and diverts them towards the supercapacitor. The effectiveness of the proposed control scheme is validated through the real-time hardware-in-the-loop (HIL) simulations on Typhoon™ HIL-402 with added uncertainties, including load variations at various temperatures and irradiances.

Study on thermal storage performance of a novel conical spiral tube heat storage system

Due to the structural advantage of the conical spiral tube, which is narrow at the top and wide at the bottom, it helps to improve the thermal response rate of the heat storage system. Therefore, this study proposes a novel conical spiral tube heat storage system. The software Fluent is used to conduct three-dimensional unsteady state calculations and investigate the effects of the conical ratio, taper, and length-to-diameter ratio on the phase change material (PCM) thermal storage performance. The results indicate that when the conical ratio is increased from 1.0 to 3.0, the PCM heat storage capacity is reduced by 1.05%, the melting time is shortened by 17.60%, the average heat storage rate is increased by 20.10%, and the heat storage efficiency is reduced by 0.10%. Continuing to increase the conical ratio, the optimization of the performance is not obvious. Subsequently, a conical ratio of 3.0 heat storage tank is used as the reference unit. When the tank taper is increased from 0 to 0.22 and the length-to-diameter ratio is increased from 1.44 to 1.85, the melting time is shortened by 7.59% and 32.62 %, the heat storage capacity is reduced by 3.45% and 9.24%, the average heat storage rate is increased by 4.47% and 34.69%, and the heat storage efficiency is reduced by 0.02% and increased by 7.99%, respectively. Continuing to increase the taper from 0.22 to 0.32 does not result in an effective improvement of the performance. This study is a good guide for the optimization of the thermal storage performance of spiral tube heat storage systems and the efficient use of solar energy.

Thermal performance of an aquifer thermal energy storage system: Insights from novel multilateral wells

Aquifer thermal energy storage (ATES) is an effective time-shifting thermal energy storage technology. Considering the enormous technical and economic input of the well pattern layout, the storage volume of a single well needs to be improved. This study proposes a novel aquifer thermal energy storage system in which several multilateral wells are side-tracked from the vertical well in the aquifer. Radial branches can enhance the connectivity of the wellbore to the aquifer. The research creates an unsteady-state 3D model to analyze the novel ATES system's fluid flow and heat transfer performance. The model is verified using experimental data. The temperature and pressure fields of the multilateral-well ATES are analyzed. Additionally, the effects of injection rate, radial branch length, number of radial branches, aquifer temperature, and aquifer thickness on system performance are studied. According to the research results, compared with the vertical wells, the performance coefficients of the multilateral hot well and cold well increase by 113.06 and 39.25, respectively, and the economic efficiency increases by 14.19% and 23.87%, respectively. The findings can provide a crucial reference for scientific research and the application of aquifer thermal energy storage systems with multilateral wells.

Energy optimization of stand-alone electrical grid considering the optimal performance of the hydrogen storage system and consumers

The surge in energy storage systems and the increasing involvement of demand-side participation can be attributed to their favorable characteristics, including their seamless integration into electrical networks and their capacity to offer operational flexibility during critical periods. This scholarly article focuses on enhancing energy utilization in an autonomous electrical grid by incorporating hydrogen storage and demand-side participation. The optimization of the stand-alone electrical grid is based on maximizing efficiency and minimizing energy consumption costs as the main objective functions are modeled. The modeling efficiency is formulated considering the ratio of the energy not supplied (ENS) to energy generation by resources. And costs of energy consumption are modeled as consumption of fuel costs by resources. The consumers’ participation is proposed based on an incentive approach to consumers for demand shaving in peak times. Also, the hydrogen storage system is installed in the stand-alone electrical grid to improve the main objectives. The particle swarm optimization (PSO) algorithm for energy optimization and solving objective functions is applied. In the end, numerical simulation is carried out in some case studies to confirm and supremacy of energy optimization with the participation of the hydrogen storage system and consumers. The case studies based on non-participation and participation of the storage system and consumers in energy management are implemented. The implementation of case studies examines the impact of both non-participation and participation of the storage system and consumers in energy management. The findings reveal that when the storage system and consumers actively participate, there is a significant improvement in efficiency and a substantial reduction in energy costs. Specifically, the efficiency is enhanced by 3% and the energy costs are reduced by 29.5% compared to the scenario where they do not participate.

Enhancing the melting performance in latent heat storage systems with fin-foam combination at high temperatures: Configurational optimization and economic assessment

High-temperature latent heat thermal energy storage is restricted by the low thermal conductivity materials. To achieve rapid heat storage, a fin-foam synergistic heat transfer enhancement is proposed to break the marginal improvement of unilateral enhancement. The effect of different enhancement methods is explored by constructing 3D numerical models. The numerical result indicates the optimal fin-foam synergistic enhancement can effectively reduce the full melting time by 59.7%, compared with the smooth-foam unilateral enhancement. Further, the relationship between temperature uniformity and thermal performance has been refined. Internal fins achieve more efficient heat transfer from the tube center to the tube edge, accompanied by a 29.1% improvement in temperature uniformity of heat transfer fluid. A comprehensive index including the pump cost is established for economic assessment. The fin-foam synergistic enhancement has been proved to be the most cost-effective, achieving relatively high performance and avoiding excessive pressure drop.

Enhanced S‐ARIMAX model performance and state‐of‐health prediction accuracy with battery pack degradation factor combinations

AbstractThis study addresses the critical need for accurate state‐of‐health (SOH) predictions in lithium‐ion batteries, crucial for maintaining efficient battery operation and extending lifespan. We propose a novel approach utilizing the Seasonal autoregressive integrated moving average with exogenous variables (S‐ARIMAX) model, integrating multiple battery degradation factors as exogenous variables for precise SOH estimation. Our methodology involves correlation analysis to identify optimal factors, which are then incorporated into distinct cases of the S‐ARIMAX model. We evaluate the model's performance using mean absolute percentage error (MAPE) and identify voltage deviation as a highly correlated exogenous variable significantly impacting predictive accuracy. Notably, our findings underscore the S‐ARIMAX model's superiority in longer cycles, demonstrating a MAPE as low as 0.1113 at 160 cycles, emphasizing the model's adeptness at capturing cyclic patterns for precise long‐term SOH forecasts. Comparing S‐ARIMAX and ARIMAX models highlights the pivotal role of seasonality, particularly in long‐term predictions. The study's quantitative findings emphasize the necessity of integrating highly correlated variables and accounting for seasonal patterns in optimizing lithium‐ion battery SOH predictions. Our approach presents practical implications for maintaining battery performance and lifespan in electric vehicles and energy storage systems, underlining the importance of selecting strongly correlated variables and integrating seasonal components for accurate and reliable SOH forecasts.

Research on intelligent control system of permanent magnet motor for high-speed flywheel energy storage system based on deep learning

With the continuous development of society, more and more people pay attention to energy issues, and the realization of energy storage has become a hot research direction today. Despite advancements, the control system of the high-speed flywheel energy storage system’s permanent magnet motor still encounters issues in effectively regulating the magnetic suspension bearing and motor speed. In addressing this issue, a technical solution involves the implementation of an intelligent control system for the high-speed flywheel energy storage system’s permanent magnet motor, utilizing deep learning principles. This innovative approach employs deep neural networks to model, optimize, and regulate the flywheel energy storage system. The essence of flywheel energy storage lies in the conversion of electrical energy into mechanical energy, followed by its reconversion into electrical energy during output. It has the advantages of high energy density, high power density, long cycle life, fast charging and discharging, maintenance-free and environmental protection. A permanent magnet motor is a motor that uses permanent magnets to generate a magnetic field. It has the characteristics of high efficiency, high power density, and low rotor loss. It remains the most widely utilized motor in flywheel energy storage systems. An intelligent control system is characterized by its use of artificial intelligence technology to adapt, self-learn, and self-organize complex systems. This system is distinguished by its robust nonlinear processing capabilities and resilience to faults. The high-speed flywheel energy storage system permanent magnet motor intelligent control system based on deep learning can improve the performance, efficiency and reliability of the flywheel energy storage system, reduce costs and risks, and is suitable for electric vehicles, rail transit, power grid frequency regulation and other fields. In this paper, the convolutional neural network and PSO algorithm are used to obtain the PSNN neural network structure to predict the speed of the motor, so as to achieve its control. And the reliability of the structure is verified by experiments.