Search Results (200)

The aim of this study was to evaluate the effect of Sida hermaphrodita harvest timing on biomass composition, properties, and methane fermentation performance. In addition, an energy–economic assessment was performed for biomass obtained at different stages of the growing season. The economic assessment assumed CHP electrical and thermal efficiencies of 38% and 47%, electricity and heat prices of 0.18 and 0.05 EUR/kWh, respectively, month-specific agrotechnical costs, and OPEX equal to 30% of total energy revenue. The biomass exhibited clear seasonal changes, transitioning from a material with high bioavailability during the summer period to a structurally more recalcitrant substrate in the autumn and winter months, as indicated by increasing lignification and fibrous fraction contents. The highest CH₄ production yields, ranging from 300 to 320 mL/g VS, and maximum production rates of up to 33.5 mL/g VS·d were obtained between June and August. In December, the CH₄ yield decreased to 180 ± 9 mL/g VS, accompanied by a substantial deterioration in kinetic performance. Despite the relatively stable theoretical methane potential, which ranged from 405 to 430 mL/g VS, its conversion efficiency declined from 77.1% in the summer period to 41.9% in the winter period. Regression analysis confirmed the key influence of the C/N ratio and total solids content, with model fits reaching R² values of 0.74–0.80, while the structure of lignocellulosic complexes had a less pronounced but still relevant effect. The maximum CH₄ production per unit cultivation area, approaching 3380 m³/ha, was achieved in July–August, reflecting a balance between high specific methane yield and biomass productivity. At the same time, the results demonstrated that the maximum biomass yield did not translate into the highest energy and economic performance. The highest net economic return, 1789 ± 330 EUR/ha, was obtained in July, despite biomass yield being 13.6% higher in September. These findings indicate a seasonal decoupling between biomass yield and energy performance, highlight biomass quality as a critical determinant of anaerobic digestion efficiency, and support harvest-date optimization as a low-cost strategy for the practical use of S. hermaphrodita in agricultural biogas plants. Further long-term continuous and semi-continuous studies are required to validate process stability and performance under industrial operating conditions. Full article

Climate change has become one of the most urgent challenges of the 21st century, shaping environmental, economic, and social dynamics on a global scale. In the Mediterranean basin, temperatures have risen by 1.5 °C, with projections suggesting a further increase of 5.6 °C by 2100. The building sector represents a critical intervention point, accounting for 30% of final energy consumption and 27% of global carbon dioxide emissions. While passive strategies mitigate these impacts, current energy policies fail to consider future variations in heating and cooling demand due to climate change. Using OpenStudio and EnergyPlus, three reference models (small office, residential building, and hospital) were simulated across five Spanish climatic areas (Almería, Córdoba, Cáceres, Lleida, León). Current conditions were compared against 2050 projections under four Shared Socioeconomic Pathways (SSP1-2.6 to SSP5-8.5) utilizing the morphing method. The results revealed a systemic shift toward cooling-dominated profiles. Small office heating demand drops by 18–34%, while cooling demand increases by 80–274%. Residential heating decreases by 19–36%, while cooling increases by 85–706%. Hospitals show milder relative variations, yet cooling demand rises 64–114%. These findings, based on thermal energy demand (kWh/m²), emphasize the need for climate-responsive design and efficient retrofitting. Conclusions regarding peak power grid stress, carbon emissions, or energy poverty are indirect implications; translating thermal demand to final energy, primary energy, or emissions requires accounting for HVAC system efficiency, energy source mix, and emission factors, which are outside the scope of this study. Full article

Photovoltaic–thermal (PVT) collectors co-generate electricity and heat—natural front ends for thermochemical energy storage (TCES)—provided the heat transfer fluid stays above the reactor’s desorption temperature. Using an eight-node model of a 0.6834 m² collector at 8.64° N whose thermal core is partially validated against measured data from the same tropical–coastal site (rooftop PV module temperature, RMSE 3.8 °C; prototype absorber-to-water heat transfer, RMSE 1.3 °C), flow-regulated to the ≈95 °C SrCl₂/NH₃ desorption threshold, we quantify the energy and exergy delivered for charging under tropical–monsoon intermittency. The 95 °C setpoint operation, the ≈5.3 h charging window, and all reported exergy yields are simulated: the built prototype delivered hot water peaking at 79 °C and did not reach the 95 °C setpoint. On a measured clear-sky day (clearness index K_t = 0.52), the collector yields 1.38 kWh of energy but only 0.43 kWh of exergy (first-law efficiency ≈ 38%; gross exergy efficiency ≈ 13%); across a 30-seed synthetic-intermittency ensemble, the exergy yield is 0.678 kWh at ≈14% gross exergy efficiency (≈52% combined first-law efficiency). In both cases, the thermal stream dominates the energy output while the electrical stream dominates the exergy output—on the sunlit day, the exergy is about 80% electrical—because 95 °C heat carries a Carnot factor (exergetic quality factor, 1 − T_a/T₇, at the instantaneous ambient dead state) of only ≈0.18 and an integrated Bejan/Kotas thermal-exergy quality of only ≈0.09. The controller holds the outlet within 1.4 K of the setpoint for ≈5.3 h, whereas no fixed flow in the 0.5–5.0 L min⁻¹ range ever reaches it: feedback control is a structural enabler, not an optimisation. On overcast days, the threshold is never reached and charging heat collapses to zero, leaving a PV-only generator. Exergy delivery is nonetheless nearly controller-independent: the accumulated exergy delivery deficit after a 50% irradiance drop is 937 kJ, a controller-independent value changing only 1.3% across a systematic 4 × 4 gain sweep (K_p 0.33–2.7×, K_d 0.25–5× of nominal), and predictive control improves it by ≤1%. For PVT–TCES at this scale, the decisive lever is deployability, not control sophistication. Full article

Calibration of crop model parameters using optimization algorithms can substantially improve model performance, particularly under different environmental scenarios. Here, we take greenhouse drip-irrigated tomato as an example. Two temperature treatments (high temperature, TH: 35 °C ≤ T_max ≤ 40 °C; non-high temperature, TD: T_max ≤ 35 °C) and two water treatments (well watered, WH: 100%E_pan; water deficit, WD: 60%E_pan, where E_pan is the pan evaporation coefficient) were combined and implemented in 2024 and 2025. Canopy cover, yield, aboveground biomass, and water consumption of tomatoes were measured, and then a global sensitivity analysis was conducted using the extended Fourier amplitude sensitivity test (EFAST). Thereafter, in order to evaluate the performance of AquaCrop-OSPy under different combinations of temperature and water conditions, the whale optimization algorithm (WOA) was coupled with the AquaCrop-OSPy model, and an automatic parameter optimization framework was developed using the aforementioned measured indicators as objective functions. The results showed that CC_x, Senescence_CD, CGC_CD, WP, HI₀, and K_cb were highly sensitive parameters of the AquaCrop-OSPy model across different temperature and water treatments. Compared with the traditional trial and error (TAE) method, WOA demonstrated superior global optimization capability and significantly improved model performance. Validation indicated that the root mean square error (RMSE) was ≤4.52% for canopy cover, ≤0.67 t/hm² for yield, and ≤0.98 t/hm² for aboveground biomass. Notably, even after WOA optimization, water consumption simulation under combined high temperature and water deficit conditions still showed some deviation, which was attributed to limitations in soil water simulation and the oversimplification of model mechanisms under combined stress. Nevertheless, the model remained reliable for estimating canopy cover, yield, and biomass, while ET simulation under combined stress should be interpreted with caution. Therefore, future improvements of AquaCrop-OSPy should focus on addressing the effects of soil water and refining the inhibitory feedback of physiological stress to better adapt the model to the combined conditions of high temperature and water deficit. Full article

Rankine cycle CO₂ pumped thermal energy storage (R-CPTES) offers high-density, emission-free grid storage, but existing designs are limited by modest turbine inlet temperatures and produce electricity only, leaving their thermal potential unused. This paper introduces a Rankine CO₂ storage cycle driven by a high-concentration parabolic dish collector (PDC) and configured solely for combined heat and power, representing a combination of point focus solar energy with CO₂ pumped thermal storage that has received limited attention in the literature. During discharge, the dish superheats the working fluid and raises the high temperature turbine inlet from 456 °C to 500 °C, boosting net power. A heating recovery exchanger placed ahead of the second regenerator then extracts useful heat from the turbine exhaust for district or process supply, without the absorption refrigeration subsystem used in comparable cooling inclusive designs. The aim is to characterise this system through energy, exergy, and parametric analysis. A closed, pinch-consistent model is developed under steady-state assumptions using the Span–Wagner equation of state, with the discharge low pressure, discharge mass flow rate, and PDC outlet temperature varied independently and jointly at a fixed 10 MPa high-pressure boundary. The analysis reveals a power-versus-heat trade-off governed by the discharge pressure and bounded by physical limits rather than interior optima, shows that the solar superheat is a prerequisite for cogeneration, and identifies the system as heat-transfer destruction dominated, with the latent cold storage the largest single source of irreversibility. At the design point the system delivers 16.1 MW of power and 2.5 MW of heat, attaining a storage round-trip efficiency of 73.2% (electricity-only), a solar-inclusive electrical efficiency of 58%, an energy utilization factor of 67%, and an overall exergy efficiency of 61.3%. A preliminary economic assessment gives a levelised cost of storage of 0.10–0.18 $/kWh, competitive with comparable CO₂ storage systems. The proposed system thus provides a simple, fossil-free cogeneration solution for high-DNI regions based on a modular, point focus solar configuration. Full article

This paper presents a battery-aware control framework for a single-phase integrated battery charger (IBC) for electric vehicles, in which the traction system is reused as part of the charging hardware. The proposed charger consists of a stator-assisted bridgeless totem-pole power-factor-correction AC–DC stage and a bidirectional buck–boost DC–DC stage connected to a 48 kWh, 400 V lithium-ion battery pack. The battery pack is modeled using a lookup-table-based equivalent circuit model with state-of-charge- and temperature-dependent open-circuit voltage and impedance parameters. A conventional double-loop PI controller is used as the baseline, while the proposed strategy combines nonlinear model predictive control, an extended Kalman filter, and lookup-table-based battery parameterization to regulate charging current under electrical and thermal constraints. The system is evaluated under 7 kW, 230 V/32 A and 22 kW, 230 V/96 A charging cases using average-model simulations, switching-model transient simulations, and finite element thermal assessment of the induction motor stator. The average-model results show stable charging from 20% to 80% SOC, with charging times of approximately 275 min at 7 kW and 90 min at 22 kW. The EKF provides bounded battery state estimation, with maximum SOC estimation errors of approximately 1.3% and 2.0% for the 7 kW and 22 kW cases, respectively, while the core-temperature estimation error converges close to zero. The switching-model results confirm feasible duty-command behavior, bounded battery-current tracking error, and a representative DC-link ripple of approximately 8 Vpp. During grid-voltage reduction, the charging current is reduced to keep the grid-current envelope within the intended limit. FEM results show that charging-only motor temperatures remain low, reaching approximately 27.39 °C at 7 kW and 38.82–38.85 °C at 22 kW. The most critical charging-related thermal case occurs at 22 kW after one hour of full-load motor operation with a 40 °C initial condition, reaching approximately 92.32 °C. Overall, these simulation-based findings support the feasibility of the proposed NMPC–EKF–LUT framework as a battery-aware supervisory control strategy for single-phase IBC operation. The proposed controller improves constraint-aware, battery state-based decision-making, while switching ripple and motor thermal response are mainly governed by the power stage, feasible current trajectory, and initial thermal condition. Full article

Associated gas in the Permian Basin is a methane-rich but spatially fragmented and intermittently available feedstock. Methane pyrolysis can convert hydrocarbons to hydrogen and solid carbon without forming process CO₂ in the reactor, but its practical value depends on the captured-gas capacity factor, feed composition, high-temperature heat supply, product purification, continuous carbon withdrawal, carbon offtake, and transparent greenhouse-gas accounting. This study presents an implemented screening model for a modular 1 million standard cubic feet per day (MMSCFD) Permian associated-gas unit. A representative Permian composition is evaluated with hydrocarbon cracking stoichiometry, catalytic and thermal conversion envelopes, a net hydrogen recovery assumption, an energy-duty allocation, a levelized-cost model, and a well-to-gate carbon-intensity model. The catalytic base case produces 3.78 t/d of saleable H₂ after 90% pressure-swing adsorption (PSA) recovery and 14.27 t/d of solid carbon; the thermal near-complete conversion bound produces 4.31 t/d of saleable H₂ and 16.15 t/d of solid carbon. At a 0.85 capacity factor, $10 million installed capital expenditure (CAPEX), 8% real discount rate, 20-year life, 10 kWh per kg H₂ energy intensity, and $0.06 per kWh electricity, the deterministic plant-gate levelized cost of hydrogen (LCOH) is $1.81 per kg H₂ at zero carbon value and $1.05 per kg H₂ at a net realized carbon value of $0.20 per kg C. Monte Carlo analysis over capacity factor, CAPEX, energy intensity, electricity price, carbon value, feed/capture cost, and yield uncertainty gives levelized cost of hydrogen values at the 10th, 50th, and 90th percentiles (P10/P50/P90) of $1.32/$1.91/$2.57 per kg H₂. The corresponding screening carbon-intensity distribution is 2.34/4.11/5.89 kg carbon dioxide equivalent (CO₂e) per kg H₂, dominated by electricity carbon intensity and upstream methane loss. Geothermal or waste-heat preheat is treated quantitatively as a partial offset to low- and mid-temperature duties, not as a replacement for high-grade 900–1200 °C trim heat. The pathway is benchmarked against steam methane reforming, autothermal reforming with carbon capture and storage, electrolysis, small-scale liquefied natural gas, and gas-to-liquids conversion. Reported LCOH values are plant-gate production costs; separate hydrogen-logistics and negative-carbon-value stress tests identify conditions under which remote delivery or carbon disposal can erode the apparent economic advantage. Full article

Improving HVAC energy efficiency while maintaining collective thermal comfort remains challenging in multi-occupant shared indoor environments, where occupants differ in thermal sensation, activity level, clothing condition, and spatial distribution. This study develops and field-validates an integrated edge-cloud IoT framework that connects non-invasive occupant-state sensing, INT8 edge thermal-sensation inference, and group-comfort-oriented HVAC setpoint optimization for classroom-based shared spaces. The proposed system integrates localized temperature–humidity sensing, vision-derived occupancy, posture, and clothing estimation, cloud-based thermal sensation model training, and edge-deployed real-time control on a HUB 8735 ULTRA device. A 4-day model-training data collection campaign with structured questionnaires was first conducted to obtain occupants’ Thermal Sensation Votes (TSVs) as ground-truth labels. The trained model was compressed from Float32 to INT8 through post-training quantization and deployed on the edge device for real-time inference. Predicted individual TSV values were then transformed into a PPD-inspired TSV-derived dissatisfaction index and used to determine the HVAC setpoint through rolling-horizon group comfort optimization. A separate eight-school-day single-blind daily-block A/B field validation was conducted, with four validation days assigned to the proposed smart control strategy and four days assigned to a fixed 25 °C baseline. The validation dataset included 2194 valid TSV questionnaire responses, which were aggregated into 116 valid 30 min classroom sessions for statistical comparison. The proposed control achieved a session-level mean TSV of −0.13, compared with −0.66 under the baseline, with Welch’s t(100) = 11.2, p < 0.001 and Cohen’s d = 2.11. Daily HVAC energy use decreased from 2.61 to 2.32 kWh/day, corresponding to a cumulative reduction of 1.16 kWh, or 11.1%, over the validation period. These results support the short-term feasibility of the proposed classroom-level human-centric HVAC control framework. However, because the validation was limited to a short-term classroom setting without full weather/load normalization, longer multi-season and multi-room studies are required to further evaluate generalizability and long-term energy performance. Full article

The decentralized deployment of photovoltaic (PV) systems in urbanized polluted mountainous basins faces unique challenges due to complex topography, persistent cloud cover and winter smog conditions. This study quantifies the atmospheric impact of localized winter haze/smog and Saharan dust intrusions on PV performance in the intermontane basin of Ioannina, NW Greece. By integrating a Digital Twin (DT) methodology with real energy production data, two PV plants were evaluated, a ground-based and a rooftop installation, to isolate the energy deficits caused by aerosol attenuation. The DT model demonstrated high accuracy (R² = 0.847) against actual power generation data for Koutselio and R² = 0.865 for Mpafra PV plants, while MBE was near zero for both sites (−0.008 kWh and −0.139 kWh, respectively). Error analysis revealed that the highest modeling discrepancies occurred during scattered clouds and intense winter haze conditions, primarily due to low spatial resolution of CAMS that fails to adequately capture localized biomass burning (BB) events. Despite the reduction in direct sunlight during extreme winter BB events, results indicate that the overall energy loss is mild. This operational stability is primarily due to the ability of c-Si modules to effectively utilize near-infrared radiation, which penetrates the low-level haze layer, alongside the thermal efficiency gains provided by low early-morning temperatures. Crucially, the installation geometry may influence system vulnerability. Direct comparisons revealed a minor power deviation of −4.8% for the ground-based Koutselio plant, while for the Mpafra site, there was a +3.2% production surplus likely linked to the high sky-view factor the rooftop installation has, which manages to capture isotropic diffuse irradiance. However, the low CAMS resolution may misclassify the haze events within the basin, further contributing to these discrepancies. On the contrary, Saharan dust intrusions caused broadband light attenuation, dropping the power production significantly on both installations. Ultimately, this research provides critical insights into the resilience of solar systems under strong air pollution events within polluted valleys in Southern Balkans, highlighting the connection between panel design and atmospheric attenuation. Full article

Existing residential buildings constructed under earlier thermal-design standards often lack effective external solar control systems. Building envelope retrofits must extend beyond mere cooling load reductions; instead, they require a holistic evaluation of summer heat rejection, winter solar gain preservation, transmitted solar exposure, and retrofit-induced embodied carbon. This study develops a screening-level method for climate-adaptive passive shading retrofits. The workflow integrates hourly solar-position reconstruction, facade irradiance mapping, shading geometry interception, and a reduced-order 2R2C thermal network. NSGA-II is used to generate Pareto-optimal alternatives, CV-TOPSIS is applied to identify representative trade-off solutions, and a life-cycle-informed carbon payback check within an A1–A4 + B6 boundary is used to test whether operational carbon savings can offset the upfront carbon of shading components and glazing replacement. Five Chinese cities—Haikou, Shanghai, Beijing, Lhasa, and Urumqi—are selected to represent the transition from cooling- to heating-dominated climates. For comparative screening, the reduced-order model shows acceptable agreement with an EnergyPlus benchmark, with NMBE, CV(RMSE), and $R^2$ values of +2.11%, 28.25%, and 0.804, respectively. The selected solutions reveal strong climate dependence in both shading morphology and carbon performance. For instance, Haikou exhibits the largest annual electricity savings (2030.3 kWh/yr) and the shortest Carbon Payback Period (1.8 years). In Lhasa, by contrast, the CV-TOPSIS-selected compromise scheme reduces the transmitted solar exposure proxy but increases annual energy use by 706.1 kWh/yr, indicating that this selected compromise, rather than fixed shading in general, is not carbon-effective within the defined boundary. The proposed method supports climate-specific retrofit screening by jointly considering heating–cooling balance, solar radiation conditions, and regional grid carbon intensity. Full article

Soybean residue (Okara), a major by-product of soybean product processing, is highly susceptible to spoilage due to its high moisture content (approximately 78% w.b.), which creates both environmental and resource-related challenges. This study aimed to develop energy-efficient drying technologies and value-added application models to improve its storage stability. The effects of heat pump drying, microwave drying, and two-stage drying on the drying kinetics, energy consumption, and product quality of okara were systematically compared. The experimental results indicated that Heat Pump Drying (HPD) at 65 °C required a prolonged drying time of 360 min. In contrast, Microwave Drying (MWD) at 2.0 W/g significantly accelerated the process, achieving the shortest drying time of 50 min (an 86.1% reduction) and lowering the specific energy consumption (SEC) to 2.2 kWh/kg (a 42.1% energy saving compared to HPD). Meanwhile, the HPD–MWD two-stage drying process offered a balanced alternative, requiring 190 min and reducing thermal risk while maintaining high efficiency. The dried okara powder contained a total dietary fiber content of 47.78%, while its water activity was maintained below 0.60. Dynamic Dew Point Isotherm (DDI) analysis confirmed a critical water activity (a_wc) of 0.66, with mathematical modeling predicting a shelf life of up to 389 days under barrier packaging conditions. In value-added application experiments, muffins containing 10% okara powder achieved sensory scores above 6 on a 9-point scale and demonstrated significantly better flavor acceptability (p = 0.0093). In summary, this study established an efficient drying and value-added application approach for okara, providing a feasible strategy for the circular use and sustainable utilization of agricultural by-products. Full article

To address the limitations of existing low-temperature evaluation methods for battery electric vehicles (BEVs) in terms of real-world road adaptability, test consistency, and multidimensional performance assessment, this study proposes a standardized on-road testing and multidimensional adaptability evaluation system for BEVs in frigid environments. To address the issues that conventional bench tests cannot adequately replicate real-world road environments, routine road tests lack consistency, and existing evaluation indicators pay insufficient attention to charging efficiency and cabin heating performance, this study defines the ambient temperature for road testing, low-speed steady-state driving conditions, and the conditions for ensuring consistency in road testing. It also establishes a cold-environment adaptability evaluation system comprising three dimensions—driving range, charging efficiency, and heating, ventilation, and air conditioning (HVAC) heating performance—and four evaluation indicators: the driving range degradation rate in cold environments, charging time per 100 km, HVAC heating duration, and HVAC heating energy consumption per unit cabin volume. Field tests were conducted on 10 representative BEVs in real-world road conditions near −20 °C in Heihe City, Heilongjiang Province, China. The results indicate that the average range degradation rate for these 10 models in cold environments was 60.7%, and approximately 60% of the vehicles could complete a 100 km charge in under 30 min; the average HVAC heating time was 34 min, with an average power consumption of 9.2 kWh. The tests also revealed that the heating efficiency and thermal comfort of single-heat-pump HVAC systems at −20 °C still have room for improvement, and that the uniformity of cabin temperature distribution and consistency in foot temperature between the left and right sides significantly affect thermal comfort. The evaluation method proposed in this study can serve as a reference for testing the cold-weather adaptability of BEVs, as well as for optimizing thermal management systems and developing vehicle performance. Full article

Proton-exchange-membrane reversible fuel cells (rPEM) are emerging as key technologies for integrated hydrogen-based energy storage systems, enabling both electricity generation and hydrogen production within a single electrochemical device. However, the transition from laboratory-scale characterization to system-level deployment requires a consistent framework linking electrochemical modeling, parameter calibration, and system design. In this work, a semi-empirical electrochemical model of an rPEM cell is developed and calibrated against literature experimental data in both fuel cell (FC) and water electrolysis (WE) modes. The calibrated model achieves high predictive accuracy, with coefficients of determination exceeding 0.997. The validated model is subsequently extended to a preliminary system-level design, enabling the development of a 100 kW reversible PEM system coupled with a 300 kW electrolyzer configuration. The proposed system features symmetric hydrogen flow (6 kg h⁻¹), a 200 kWh hydrogen storage buffer, and operating conditions of 2.5 bar/70 °C in FC mode and 30 bar/65 °C in WE mode. Thermal effects and efficiency trends are analyzed, highlighting the critical role of heat management and balance of plant proposed design. The proposed methodology provides a consistent framework for scaling rPEM technology toward industrial applications. Full article

Energy and exergy analyses were conducted on a triple-pass seawater reverse osmosis desalination system to evaluate thermodynamic performance and identify primary sources of irreversibility. A comprehensive simulation model, developed in IPSEpro (Version 7.0) and validated against manufacturer data, demonstrated strong agreement with the reported values. Exergetic efficiency of the reverse osmosis (RO) units increased across the passes, from 57% in the first pass to 80% and 78% in the second and third passes, respectively, while exergy destruction decreased correspondingly from approximately 375 kW in the first pass to 120 kW and 130 kW in the second and third passes. The pumping system, particularly the main high-pressure pump, was responsible for 49% of total exergy destruction, followed by the first RO unit at 23%. The impacts of feed water temperature, high-pressure pump pressure, and water recovery ratio (RC) on exergetic efficiency, specific energy consumption, and permeate flow rate were systematically assessed. Increasing the feed water temperature from 15 °C to 33 °C enhanced exergetic efficiency from 27.8% to 29.9% and reduced total exergy destruction from 1622 to 1582 kW, supporting the integration of hybrid RO-thermal desalination systems. The first-pass recovery ratio emerged as the most influential operational parameter overall, with exergetic efficiency rising from 25.1% to 33.7% as RC₁ increased from 0.35 to 0.60. Analysis of the overall recovery ratio identified RC = 0.39 as a practical operating target that balances specific energy consumption of 4.05 kWh/m³ and exergy destruction of 1700 kW, offering the most favourable compromise between energy efficiency and thermodynamic performance. The results presented here provide practical guidance and recommendations for the optimization of the performance of large-scale multi-pass reverse osmosis seawater desalination plants. Full article

This article presents an experimental–computational methodology for evaluating the state of charge (SoC), energy consumption, terminal-voltage behavior, and driving range of a 350 W electric scooter powered by a 36 V, 7.8 Ah lithium-ion battery. The test was carried out using a 117 s elementary urban driving cycle derived from the low-speed section of the New European Driving Cycle (NEDC) and limited to the 32 km/h operating speed of the scooter. Laboratory measurements were performed on rollers under controlled conditions. Battery current and terminal voltage were recorded during the discharge test. The experimental SoC was reconstructed from the measured current by trapezoidal Coulomb counting. The voltage-derived SoC values included in the original laboratory file were kept only for traceability, since they did not correspond to current integration. A MATLAB/Simulink model was developed to reproduce the driving cycle, longitudinal vehicle dynamics, DC motor demand, battery current, and SoC evolution. The valid experimental endpoint occurred at 5233 s, when the terminal voltage reached 31.50 V. At this point, the tested distance was 16.49 km, the discharged capacity was 5.817 Ah, and the final experimental SoC was 25.42%. The simulation produced a discharged capacity of 5.147 Ah and a final SoC of 34.01%, with a charge deviation of 11.51%. Energy consumption was also evaluated from the measured and simulated electrical power. The experimentally integrated discharged energy was 208.10 Wh, equivalent to 12.62 Wh/km. The simulated electrical demand was 184.41 Wh, equivalent to 11.18 Wh/km. A semiempirical terminal-voltage reconstruction, based on the simulated SoC, current demand, an open-circuit-voltage curve, and a fixed internal resistance, reproduced the global voltage-decay trend observed in the experiment. The simplified model captured the general discharge behavior, although it underestimated the measured charge and energy demand. The proposed workflow provides a reproducible basis for comparing manufacturer-declared range, laboratory measurements, current-based SoC reconstruction, energy consumption, and simplified simulation results in light electric vehicles. Full article