Search Results (1,317)

This paper presents a calibrated and dynamically responsive simulation framework for hybrid energy systems that integrate Proton Exchange Membrane Fuel Cells (PEMFCs) and batteries, targeting applications in light commercial vehicles (LCVs). The aim is to support the design and assessment of energy management strategies (EMS) under realistic operating conditions. A publicly available PEMFC model is used as the starting point. To improve its representativeness, calibration is performed using experimental polarization curve data, enhancing the accuracy of the stack voltage model, and the air compressor model—critical for maintaining stable fuel cell operation—is adjusted to reflect measured transient responses, ensuring realistic system behavior under varying load demands. Quantitatively, the calibration results are strong: the R² values of both the fuel cell polarization curve and the overall system efficiency are around 0.99, indicating excellent agreement with experimental data. The calibrated model is embedded within a complete hybrid vehicle powertrain simulation, incorporating longitudinal dynamics and control strategies for power distribution between the battery and fuel cells. Simulations conducted under WLTP driving cycles confirm the model’s ability to replicate key behaviors of PEMFC-battery hybrid systems, particularly with respect to dynamic energy flow and system response. In conclusion, this work provides a reliable and high-fidelity simulation environment based on empirical calibration of key subsystems, which is well suited for the development and evaluation of advanced EMS algorithms. Full article

Advancements in battery technology, marked by reduced costs and enhanced efficiency, are steadily making electric vehicles (EVs) more accessible to consumers. This trend is fueling global growth in EV fleet sizes, allowing EVs to compete directly with internal combustion engine vehicles. However, this rapid growth in EV numbers is likely to introduce challenges to the power grid, necessitating effective load management strategies. This work proposes an optimization method where EV load management is integrated into the Transmission Constrained Unit Commitment Problem (TCUCP). A Differential Evolution (DE) variant, enhanced with heuristic repair sub-algorithms, is employed to address the TCUCP. The heuristic sub-algorithms, adapted from earlier approaches to the simpler Unit Commitment Problem (UCP), are updated to incorporate power flow constraints and ensure the elimination of transmission line violations. Additionally, new repair mechanisms are introduced that combine priority lists with grid information to minimize violation. The proposed formulation considers EVs as both flexible loads and energy sources in a large urban environment powered by two grid nodes, accounting for the vehicles’ daily movement patterns. The algorithm exhibits exceptionally fast convergence to a feasible solution in fewer than 150 generations, despite the nonlinearity of the problem. Depending on the scenario, the total production cost is reduced by up to 45% within these generations. Moreover, the results of the proposed model, when compared with a MILP algorithm, achieve values with a relative difference of approximately 1%. Full article

As a novel energy storage technology, seawater batteries exhibit significant application potential across various domains, including marine exploration, underwater communication, and island power supply. However, the deep-sea low-temperature environment adversely affects the performance of seawater battery systems. This paper proposes a seawater metal–air battery system equipped with a preheater (SMAB-P). This innovative system establishes stable natural circulation and utilizes the high-temperature seawater within the system to preheat the incoming low-temperature seawater, thereby effectively enhancing battery performance. It was found that, compared with the SMAB system without a preheater, when achieving a heat recovery rate of 100% the average temperature of seawater in the electrode plate area of the SMAB-P system can be increased by 54%. Consequently, the electrical conductivity of seawater within the system can be increased by approximately 20%, leading to a significant reduction in ohmic losses and an enhancement in the load voltage of the battery. Furthermore, increasing either the height or width of the electrode plate can enhance self-driven force and circulation flow rate, as well as both average and maximum temperatures of seawater in the electrode plate area to some extent. Reducing the annular space of the preheater can significantly increase the seawater temperature within the system, but excessive reduction may hinder the effective replacement of fresh seawater in the system. It is also noted that seawater velocity in the electrode plate channels remains relatively low and evenly distributed while exhibiting very small temperature variation. Full article

The transition to decentralized renewable energy systems has highlighted the role of AC microgrids and battery energy storage systems in achieving operational efficiency and sustainability. This study proposes an improved energy management system for AC MGs based on a tuned Parallel Population-Based Genetic Algorithm for the optimal operation of batteries under variable generation and demand. The optimization framework minimizes power losses, emissions, and economic costs through a master–slave strategy, employing hourly power flow via successive approximations for technical evaluation. A comprehensive assessment is carried out under both grid-connected and islanded operation modes using a common test bed, centered on a flexible slack bus capable of adapting to either mode. Comparative analyses against Particle Swarm Optimization and the Vortex Search Algorithm demonstrate the superior accuracy, stability, and computational efficiency of the proposed methodology. In grid-connected mode, the Parallel Population-Based Genetic Algorithm achieves average reductions of 1.421% in operational cost, 4.383% in power losses, and 0.183% in CO₂ emissions, while maintaining standard deviations below 0.02%. In islanded mode, it attains reductions of 0.131%, 4.469%, and 0.184%, respectively. The improvement in cost relative to the benchmark exact methods is 0.00158%. Simulations on a simplified 33-node AC MG with actual demand and generation profiles confirm significant improvements across all performance metrics compared to previous research works. Full article

State-of-charge (SOC) and temperature inconsistencies among lithium-ion battery cells can significantly degrade the performance, safety, and lifespan of battery packs. To address this issue, this paper proposes a dynamic balancing strategy that simultaneously regulates both SOC and cell temperature in real time. Each battery cell is connected to an individual Boost converter, enabling independent control of energy flow. An outer loop is adopted to stabilize the pack-level bus voltage. The balancing factors for SOC and temperature are adaptively fused using a Particle Swarm Optimization (PSO) algorithm, which dynamically adjusts the weightings based on real-time operating conditions. This approach allows the controller to prioritize either thermal or electrical balance when needed, ensuring robust performance under varying load and environmental disturbances. Simulation-based validation on a multi-cell lithium-ion pack demonstrates that the proposed method effectively reduces SOC and temperature deviation, improves pack-level energy utilization, and extends operational stability compared to fixed-weight balancing strategies. Full article

Optimizing the power allocation and capacity configuration of hybrid energy storage systems (HESS) is crucial for enhancing grid stability, power quality and renewable energy utilization in wind–solar complementary microgrids. However, the conventional configuration methods exhibit inaccuracy and low reliability. To achieve the optimal capacity configuration of HESS in wind–solar complementary microgrids, a power allocation strategy and a capacity optimization configuration model for HESS consisting of vanadium redox flow batteries (VRBs) and supercapacitors (SCs) were proposed based on parameter-optimized variational mode decomposition (VMD). Firstly, the number of mode decomposition (K) and the penalty factor (α) of VMD were optimized using the random walk grey wolf optimizer (RW-GWO) algorithm, and the HESS power signal was decomposed by RW-GWO-VMD. Secondly, an optimal capacity configuration model was formulated, taking into account the whole life cycle cost of HESS, and particle swarm optimization (PSO) algorithm was applied to optimize HESS capacity while satisfying operational constraints on charge/discharge power, state of charge (SOC) range, and permissible rates of load deficit and energy loss. Thirdly, the optimal capacity allocation was obtained by minimizing the whole life cycle cost of HESS, with the frequency division threshold N serving as the optimization parameter. Finally, comprehensive comparison and analysis of proposed methods were conducted through simulation experiments. The results demonstrated that the whole life cycle cost of RW-GWO-VMD was 7.44% lower than that of EMD, 1.00% lower than that of PSO-VMD, 0.72% lower than that of AOA-VMD, and 0.27% lower than that of GWO-VMD. Full article

The literature clearly indicates that both academia and industry are strongly committed to developing comprehensive processes for spent Li-ion battery (LIB) recycling. In this regard, the current study presents an original contribution by providing a quantitative assessment of a large-scale recycling plant designed for the treatment of completely spent LIBs. In addition to a concept of the basic process, this assessment also considers a case study of a thermal integration and CO₂ capture subsystem. Process flow modeling software was used to evaluate the contribution of all process steps and equipment to overall energy consumption and to mass balance the data required for the technical assessment of the large-scale recycling plant. To underline the advantages and identify the optimal novel process concept, several key performance indicators were determined, such as recovery efficiency, specific energy/material consumption, and specific CO₂ emissions. In addition, the economic potential of the recycling plants was evaluated for the defined case studies based on capital and O&M costs. The results indicate that, even with CO₂ capture applied, the thermally integrated process with the combustion of hydrogen produced in the recycling plant remains the most promising large-scale configuration for spent LIB recycling. Full article

Aqueous redox flow batteries (ARFBs) have attracted significant attention in the field of electrochemical energy storage due to their high intrinsic safety, low cost, and flexible system configuration. However, the advancement of this technology is still hindered by several critical challenges, including capacity decay, structural optimization, and the design and application of key materials as well as their performance within battery systems. Addressing these issues requires systematic theoretical foundations and scientific guidance. Numerical modeling has emerged as a powerful tool for investigating the complex physical and electrochemical processes within flow batteries across multiple spatial and temporal scales. It also enables predictive performance analysis and cost-effective optimization at both the component and system levels, thus accelerating research and development. This review provides a comprehensive overview of recent progress in the modeling of ARFBs. Taking the all-vanadium redox flow battery as a representative example, we summarize the key multiphysics phenomena involved and introduce corresponding multi-scale modeling strategies. Furthermore, specific modeling considerations are discussed for phase-change ARFBs, such as zinc-based ones involving solid–liquid phase transition, and hydrogen–bromine systems characterized by gas–liquid two-phase flow, highlighting their distinctive features compared to vanadium systems. Finally, this paper explores the major challenges and potential opportunities in the modeling of representative ARFB systems, aiming to provide theoretical guidance and technical support for the continued development and practical application of ARFB technology. Full article

This paper presents a comparative study of data-driven modeling approaches for vanadium redox flow batteries (VRFBs), utilizing Multiple Linear Regression (MLR) and Random Forest (RF) algorithms. Experimental voltage–capacity datasets from a 1 kW/1 kWh VRFB system were digitized, processed, and used for model training, validation, and testing. The MLR model, built using eight optimized features, achieved a mean error (ME) of 0.0204 V, a residual sum of squares (RSS) of 8.87, and a root mean squared error (RMSE) of 0.1796 V on the test data, demonstrating high predictive performance in stationary operating regions. However, it exhibited limited accuracy during dynamic transitions. Optimized through out-of-bag (OOB) error minimization, the Random Forest model achieved a training RMSE of 0.093 V and a test RMSE of 0.110 V, significantly outperforming MLR in capturing dynamic behavior while maintaining comparable performance in steady-state regions. The accuracy remained high even at lower current densities. Feature importance analysis and partial dependence plots (PDPs) confirmed the dominance of current-related features and SOC dynamics in influencing VRFB terminal voltage. Overall, the Random Forest model offers superior accuracy and robustness, making it highly suitable for real-time VRFB system monitoring, control, and digital twin integration. This study highlights the potential of combining machine learning algorithms with electrochemical domain knowledge to enhance battery system modeling for future energy storage applications. Full article

This paper presents an advanced energy management system (EMS) for optimizing power distribution in a battery/ultracapacitor (UC) hybrid energy storage system (HESS) for electric vehicles (EVs). The proposed EMS accounts for all energy flow scenarios within a practical driving cycle. A regenerative braking control strategy is developed to maximize kinetic energy recovery using an induction motor, efficiently distributing the recovered energy between the UC and battery. Additionally, a power flow management approach is introduced for both motoring (discharge) and braking (charge) operations via bidirectional buck–boost DC-DC converters. In discharge mode, an optimal distribution factor is dynamically adjusted to balance power delivery between the battery and UC, maximizing efficiency. During charging, a DC link voltage control mechanism prioritizes UC charging over the battery, reducing stress and enhancing energy recovery efficiency. The proposed EMS is validated through simulations and experiments, demonstrating significant improvements in vehicle acceleration, energy efficiency, and battery lifespan. Full article

Internal fins are commonly utilized as a passive technique to enhance natural convection, but their efficiency depends on complex interplay between fin design, material properties, and convective strength. This study presents an extensive numerical analysis of buoyancy-driven flow in square cavities containing a single horizontal fin on the hot wall. Over 9000 simulations were conducted, methodically varying the Rayleigh number (Ra = 10 to 10⁵), Prandtl number (Pr = 0.1 to 10), and fin characteristics, such as length, vertical position, thickness, and the thermal conductivity ratio (up to 1000), to assess their overall impact on thermal efficiency. Thermal enhancements compared to scenarios without fins are quantified using local and average Nusselt numbers, as well as a Nusselt number ratio (NNR). The results reveal that, contrary to conventional beliefs, long fins positioned centrally can actually decrease heat transfer by up to 11.8% at high Ra and Pr due to the disruption of thermal plumes and diminished circulation. Conversely, shorter fins located near the cavity’s top and bottom wall edges can enhance the Nusselt numbers for the hot wall by up to 8.4%, thereby positively affecting the development of thermal boundary layers. A U-shaped Nusselt number distribution related to fin placement appears at Ra ≥ 10³, where edge-aligned fins consistently outperform those positioned mid-height. The benefits of high-conductivity fins become increasingly nonlinear at larger Ra, with advantages limited to designs that minimally disrupt core convective patterns. These findings challenge established notions regarding passive thermal enhancement and provide a predictive thermogeometric framework for designing enclosures. The results can be directly applied to passive cooling systems in electronics, battery packs, solar thermal collectors, and energy-efficient buildings, where optimizing heat transfer is vital without employing active control methods. Full article

Aqueous organic redox flow batteries (AORFBs) represent an advancing class of electrochemical energy storage systems showing considerable promise for large-scale grid integration due to their unique aqueous organic chemistry. However, the use of small-molecule active materials in AORFBs is significantly limited by the issue of stability and crossover. To address these challenges, we designed a high-water-solubility polymer cathode material, P-T-S, which features a polyvinylimidazole backbone functionalized with 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) and sulfonate groups. P-T-S exhibits a solubility of 34 Ah L⁻¹ in water and 31 Ah L⁻¹ in 1.0 M NaCl aqueous solution (NaCl_aq). When paired with methyl viologen to assemble a pH-neutral AORFB with a theoretical capacity of 15 Ah L⁻¹, the system exhibits a material utilization rate of 92.0%, an average capacity retention rate of 99.74% per cycle (99.74% per hour), and an average Coulombic efficiency of 98.69% over 300 consecutive cycles at 30 mA cm⁻². This work provides a new design strategy for polymer materials for high-performance AORFBs. Full article

Railway systems occupy a predominant role in urban transport, providing efficient, high-capacity mobility. Progress in rail transport allows fast traveling, whilst environmental concerns and CO₂ emissions are on the rise. The integration of railway systems with renewable energy source (RES)-based stations presents a promising avenue to improve the sustainability, reliability, and efficiency of urban transport networks. A storage system is needed to both ensure a continuous power supply and meet train demand at the station. Batteries (BTs) offer high energy density, while supercapacitors (SCs) offer both a large number of charge and discharge cycles, and high-power density. This paper proposes a hybrid RES (photovoltaic and wind), combined with batteries and supercapacitors constituting the hybrid energy storage system (HESS). One major drawback of trains is the long charging time required in stations, so they have been fitted with SCs to allow them to charge up quickly. A new fuzzy energy management strategy (F-EMS) is proposed. This supervision strategy optimizes the power flow between renewable energy sources, HESS, and trains. DC bus voltage regulation is involved, maintaining BT and SC charging levels within acceptable ranges. The simulation results, carried out using MATLAB/Simulink, demonstrate the effectiveness of the suggested fuzzy energy management strategy for various production conditions and train demand. Full article

Inspired by the Toyota Mirai, this study presents a high-fidelity data-driven approach for modelling and simulation of a fuel cell hybrid electric powertrain. This study utilises technical assessment data sourced from Argonne National Laboratory’s publicly available report, faithfully modelling most of the vehicle subsystems as data-driven entities. The simulation framework is developed in the MATLAB/Simulink environment and is based on a power dynamics approach, capturing nonlinear interactions and performance intricacies between different powertrain elements. This study investigates subsystem synergies and performance boundaries under a combined driving cycle composed of the NEDC, WLTP Class 3 and US06 profiles, representing urban, extra-urban and aggressive highway conditions. To emulate the real-world load-following strategy, a state transition power management and allocation method is synthesised. The proposed method dynamically governs the power flow between the fuel cell stack and the traction battery across three operational states, allowing the battery to stay within its allocated bounds. This simulation framework offers a near-accurate and computationally efficient digital counterpart to a commercial hybrid powertrain, serving as a valuable tool for educational and research purposes. Full article

An efficient integrated energy system (IES) can enhance the potential of building energy conservation and carbon mitigation. However, imbalances between user-side demand and supply side output present formidable challenges to the operational dispatch of building energy systems. To mitigate heat rejection and improve dispatch optimization, an integrated building energy system incorporating waste heat recovery via an absorption heat pump based on the flow temperature model is adopted. A comprehensive analysis was conducted to investigate the correlation among heat pump operational strategies, thermal comfort, and the dynamic thermal storage capacity of piping network systems. The optimization calculations and comparative analyses were conducted across five cases on typical season days via the CPLEX solver with MATLAB R2018a. The simulation results indicate that the operational modes of absorption heat pump reduced the costs by 4.4–8.5%, while the absorption rate of waste heat increased from 37.02% to 51.46%. Additionally, the utilization ratio of battery and thermal storage units decreased by up to 69.82% at most after considering the pipeline thermal inertia and thermal comfort, thus increasing the system’s energy-saving ability and reducing the pressure of energy storage equipment, ultimately increasing the scheduling flexibility of the integrated building energy system. Full article