Search Results (252)

The optimal control of cooling water systems is of great significance for energy saving in chiller plants. Previously optimal control methods optimize the flow rate, temperature or temperature difference setpoints but cannot control pumps and cooling tower fans directly. This study proposes a direct optimal control method for pumps and fans based on derivative control strategy by decoupling water flow rate optimization and airflow rate optimization, which can make the total power of chillers, pumps and fans approach a minimum. Simulations for different conditions were performed for the validation and performance analysis of the optimal control strategy. The optimization algorithms and implementation methods of direct optimal control were developed and validated by experiment. The simulation results indicate that total power approaches a minimum when the derivative of total power with respect to water/air flow rate approaches zero. The power-saving rate of the studied chiller plant is 13.2% at a plant part-load ratio of 20% compared to the constant-speed pump/fan mode. The experimental results show that the direct control method, taking power frequency as a controlled variable, can make variable frequency drives regulate their output frequencies to be equal to the optimized power frequencies of pumps and fans in a timely manner. Full article

To address the complex trade-offs among charging efficiency, battery lifespan, energy efficiency, and safety in high-power electric vehicle (EV) fast charging, this paper presents an intelligent control framework based on contrastive learning and manifold-constrained multi-objective optimization. A multi-physics coupled electro-thermal-chemical model is formulated as a Mixed-Integer Nonlinear Programming (MINLP) problem, incorporating both continuous and discrete decision variables—such as charging power and cooling modes—into a unified optimization framework. An environment-adaptive optimization strategy is also developed. To enhance learning efficiency and policy safety, a contrastive learning–enhanced policy gradient (CLPG) algorithm is proposed to distinguish between high-quality and unsafe charging trajectories. A manifold-aware action generation network (MAN) is further introduced to enforce dynamic safety constraints under varying environmental and battery conditions. Simulation results demonstrate that the proposed framework reduces charging time to 18.3 min—47.7% faster than the conventional CC–CV method—while achieving 96.2% energy efficiency, 99.7% capacity retention, and zero safety violations. The framework also exhibits strong adaptability across wide temperature (−20 °C to 45 °C) and aging (SOH down to 70%) conditions, with real-time inference speed (6.76 ms) satisfying deployment requirements. This study provides a safe, efficient, and adaptive solution for intelligent high-power EV fast-charging. Full article

Harnessing Europe’s strong wave energy could support net-zero emissions goals, but extreme ocean loads still make wave energy expensive and delay the rollout of commercial wave-energy converters (WECs). To address this, the twin-floater CECO WEC has been redesigned into a single-pivot device called the Pivoting WEC (PWEC), which includes a passive duck diving survival mode to reduce extreme wave impacts. Its performance is evaluated using detailed wave simulations based on Reynolds-Averaged Navier–Stokes (RANS) equations and the Volume-of-Fluid (VoF) method in OpenFOAM-olaFlow, which is validated with data from small-scale (1:20) wave tank experiments. Extreme non-breaking and breaking waves are simulated based on 100-year hindcast data for the case study site of Matosinhos (Portugal) using a modified Miche criterion. These are validated using data of surface elevation and force sensors. Wave height errors averaged 5.13%, and period errors remain below 0.75%. The model captures well major wave loads with a root mean square error down to 47 kN compared to a peak load of 260 kN and an R² up to 0.80. The most violent plunging waves increase peak forces by 5 to 30% compared to the highest non-breaking crests. The validated numerical approach provides accurate extreme load predictions and confirms the effectiveness of the PWEC’s passive duck diving survival mode. The results contribute to the development of structurally resilient WECs, supporting the progress of WECs toward higher readiness levels. Full article

Perfect absorbers operating in the terahertz (THz) band are key enablers for next-generation wireless systems. However, conventional metal–dielectric designs suffer from Ohmic losses and limited reconfigurability. Here, we propose an all-dielectric indium antimonide (InSb) cylindrical pillar metasurface that achieves near-unity absorption at $f_0=1.83$ THz with a high quality factor of $Q=72.3$. Critical coupling between coexisting electric and magnetic dipoles enables perfect impedance matching, while InSb’s low damping minimizes energy loss. The resonance is tunable via temperature and magnetic bias at sensitivities of $S_T\approx 2.8\mathrm{GHz}·{\mathrm{K}}^{-1}$, $S_B^{\mathrm{TE}}\approx -132.7\mathrm{GHz}·{\mathrm{T}}^{-1}$, and $S_B^{\mathrm{TM}}\approx -34.7\mathrm{GHz}·{\mathrm{T}}^{-1}$, respectively, without compromising absorption strength. At zero magnetic bias ($B=0$), the metasurface is polarization-independent under normal incidence; under magnetic bias ($B\ne 0$), it maintains near-unity absorbance for both TE and TM, while the resonance frequency becomes polarization-dependent. Additionally, the 90% absorptance bandwidth ($\Delta f_{A\ge 0.9}$) can be modulated from 8.3 GHz to 3.3 GHz with temperature, or broadened from 8.5 GHz to 14.8 GHz under magnetic bias. This allows gapless suppression of up to 14 consecutive 1 GHz-spaced channels. This standards-agnostic bandwidth metric illustrates dynamic spectral filtering for future THz links and beyond-5G/6G research. Owing to its sharp selectivity, dual-mode tunability, and metal-free construction, the proposed absorber offers a compact and reconfigurable platform for advanced THz filtering applications. Full article

Biorobotics leverages the principles of natural locomotion to enhance the mobility of bioinspired aquatic robots. Among various swimming modes, anguilliform locomotion is particularly recognized as an energy-efficient mode incorporating complex multiphysics. Due to whole-body undulation, the determination of the anguilliform swimmer’s direction is not trivial. Furthermore, the neuromuscular mechanism that controls straight swimming is not fully understood. This study investigates the challenge of predicting and controling the gross motion trajectory of a soft robot that utilizes anguilliform swimming. The robot consists of a six-segment continuous body, where each segment is actuated with pneumatic artificial muscles. A mode extraction technique based on dynamic mode decomposition (DMD) is proposed to identify the robot’s future state. Using the complex-variable delay embedding (CDE) technique, the CDE DMD algorithm is developed to predict the robot trajectory trend. To vary the robot direction, a hypothesis that asymmetric sidewise actuation results in slightly different fluid velocities between the left and right sides of the robot was investigated using COMSOL Multiphysics^® 6.2. The simulation results demonstrate the CDE DMD’s ability to predict gross motion across various scenarios. Furthermore, integrating the prediction model with the asymmetric actuation rule provides a control strategy for directional stability of the robot. Simulations of the closed-loop system with non-zero initial pose (step response) indicate the performance in maintaining straight-line swimming with approximately a 60s settling time. Full article

The transportation industry significantly contributes to greenhouse gas (GHG) emissions. Federal and provincial governments have implemented strategies to decrease dependence on gasoline and diesel fuels. This encompasses promoting the adoption of electric cars (EVs) and biofuel alternatives, investing in renewable energy sources, and enhancing public transit systems. There is a growing focus on enhancing infrastructure to facilitate active transportation modes like cycling and walking, which provide the combined advantages of decreasing emissions and advancing public health. In this paper, we propose a System Dynamics simulation model for evaluating factors for the adoption of alternative-fuel vehicles such as EVs, biofuel vehicles, bus, bikes, and hydrogen vehicles. Five factors—namely, customer awareness, government initiatives, cost of vehicles, cost of fuels, and infrastructure developments—to increase the adoption of alternative-fuel vehicles are studied. Two scenarios are modeled: A baseline scenario that follows the existing trends in transportation (namely the use of gasoline vehicles), Scenario 1, which prioritizes greater adoption of electric vehicles (EVs) and biofuel-powered vehicles, and Scenario 2, which prioritizes hydrogen fuel-based vehicles and improves biking culture. The simulation findings show that all scenarios achieve reductions in GHG emissions compared to the baseline, with Scenario 2 showing the lowest emissions. The proposed work is useful for transport decision makers and municipal administrators in devising policies for reducing overall GHG emissions, and this also aligns with Canada’s net zero goals. Full article

Medium-voltage energy storage converter equipment is an important component of the new generation of ship power and power systems. Virtual space vector pulse width modulation, as a modulation optimization method to improve the neutral-point voltage imbalance in medium- and high-voltage multilevel energy storage converters, has become a research hotspot for T-type three-level energy storage inverter modulation methods due to its significant balancing effect and simple implementation. However, the current research method of constructing virtual vectors through redundant small vectors has limitations in regulating the neutral-point potential under full (especially high) modulation ratios. This paper proposes a modulation method that uses hybrid variable virtual small vectors and virtual medium vectors through optimization selection and reconstruction of basic vectors. This method ensures that the neutral-point charge change of the vector is zero and the common-mode voltage is minimized within the switching period under the full modulation ratio, achieving the purpose of controlling the neutral-point voltage balance and suppressing the common-mode voltage. Finally, simulation and experimental results show that the proposed method has good neutral-point voltage regulation and common-mode voltage suppression capabilities within the full modulation ratio range, and the system also has strong robustness and adaptability under different load conditions. Full article

Hybrid electric vehicles (HEVs) have gained significant attention for their superior energy efficiency and are becoming a predominant mode of urban transportation. The DC/DC converter plays a critical role in HEV energy management systems, especially in matching the voltage levels between the battery and DC bus. This paper proposes a novel high-gain DC/DC converter with a wide input voltage range based on coupled inductors. The innovation lies in the integration of a resonant cavity and the simultaneous realization of zero-voltage switching (ZVS) and zero-current switching (ZCS), effectively reducing both voltage/current stresses on the power switches and switching losses. Compared with conventional topologies, the proposed design achieves higher voltage gain without extreme duty cycles, improved conversion efficiency, and enhanced reliability. Detailed operating principles are analyzed, and design conditions for voltage stress reduction, gain extension, and soft switching are derived. The simulation model has been conducted in a PSIM environment, and a 300 W experimental prototype, implemented using a dsPIC33FJ64GS606 digital controller, has been established and demonstrates 93% peak efficiency at a 10 times voltage gain. The performance and practical feasibility of the proposed topology have been evaluated by both simulation and experiments. Full article

This paper presents a literature review of low-power hybrid wind–photovoltaic (PV) systems and introduces a 3 m diameter prototype rotor featuring twelve PV-coated pivoting blades stiffened by a peripheral rim. Existing solutions—foldable umbrella concepts, Darrieus rotors with PV-integrated blades, and morphing blades—are surveyed, and current gaps in simultaneous wind + PV co-generation on a single moving structure are highlighted. Key performance indicators such as power coefficient (C_p), DC ripple, cell temperature difference (ΔT), and levelised cost of energy (LCOE) are defined, and an integrated assessment methodology is proposed based on blade element momentum (BEM) and computational fluid dynamics (CFD) modelling, dynamic current–voltage (I–V) testing, and failure modes and effects analysis (FMEA) to evaluate system performance and reliability. Preliminary results point to moderate aerodynamic penalties (ΔC_p ≈ 5–8%), PV output during rotation equal to 15–25% of the nominal PV power (P_PV), and an estimated 70–75% reduction in blade–root bending moment when the peripheral ring converts each blade from a cantilever to a simply supported member, resulting in increased blade stiffness. Major challenges include the collective pitch mechanism, dynamic shading, and wear of rotating components (slip rings); however, the suggested technical measures—maximum power point tracking (MPPT), string segmentation, and redundant braking—keep performance within acceptable limits. This study concludes that the concept shows promise for distributed microgeneration, provided extensive experimental validation and IEC 61400-2-compliant standardisation are pursued. This paper has a dual scope: (i) a concise literature review relevant to low-Re flat-blade aerodynamics and ring-stiffened rotor structures and (ii) a multi-fidelity aero-structural study that culminates in a 3 m prototype proposal. We present the first evaluation of a hybrid wind–PV rotor employing untwisted flat-plate blades stiffened by a peripheral ring. Using low-Re BEM for preliminary loading, steady-state RANS-CFD (k-ω SST) for validation, and elastic FEM for sizing, we assemble a coherent load/performance dataset. After upsizing the hub pins (Ø 30 mm), ring (50 × 50 mm), and spokes (Ø 40 mm), von Mises stresses remain < 25% of the 6061-T6 yield limit and tip deflection ≤ 0.5%·R acrosscut-in (3 m s⁻¹), nominal (5 m s⁻¹), and extreme (25 m s⁻¹) cases. CFD confirms a broad efficiency plateau at λ = 2.4–2.8 for β ≈ 10° and near-zero shaft torque at β = 90°, supporting a three-step pitch schedule (20° start-up → 10° nominal → 90° storm). Cross-model deviations for C_p, torque, and pressure/force distributions remain within ± 10%. This study addresses only the rotor; off-the-shelf generator, brake, screw-pitch, and azimuth/tilt drives are intended for later integration. The results provide a low-cost manufacturable architecture and a validated baseline for full-scale testing and future transient CFD/FEM iterations. Full article

Global Navigation Satellite System (GNSS) buoys are widely used to retrieve wave parameters such as significant wave heights (SWHs) and dominant wave periods. In addition to the statistical methods employed to estimate wave parameters, spectral-analysis-based approaches are also frequently utilized to analyze them. This study presents statistical and spectral methods for retrieving wave parameters at GNSS buoy positioning resolution in the Huanghai Sea area. To verify the method’s effectiveness, the zero-crossing method and three spectral analysis techniques (periodogram, autocorrelation function, and autoregressive model methods) were used to estimate wave height and period for comparison. The vertical positioning resolution was decomposed into low-frequency ocean-tide level information and high-frequency wave height and period information with the Complete Ensemble Empirical Mode Decomposition (CEEMD) method and moving average filtering. The horizontal positioning results and velocity parameters were used to determine the wave direction using directional spectrum analysis. The results show that the three spectral methods yield consistent effective wave heights, with a maximum difference of 0.02 s in the wave period. Compared with the zero-crossing method results, the wave height and period obtained through spectral analysis differ by 0.05 m and 0.79 s, respectively, while the average wave height and period differ by 0.09 m and 0.08 s, respectively. The GNSS-derived wave heights also closely match tidal gauge observations, confirming the method’s validity. Directional spectrum analysis indicates that wave energy is concentrated in the 0.2–0.25 Hz frequency band and within a directional range of 0° ± 30°, with a dominant northward propagation trend. These findings demonstrate that the proposed approach can provide high accuracy and physical consistency for GNSS-based wave monitoring under complex sea conditions. Full article

This work investigates the intricate dynamics of the Carreau hybrid nanofluid’s inclined magnetohydrodynamic (MHD) flow, exploring both active and passive control modes. The study incorporates critical factors, including Arrhenius activation energy across a stretched sheet, chemical interactions, and nonlinear thermal radiation. The formulation of the boundary conditions and governing equations is inherently influenced by symmetric considerations in the physical geometry and flow assumptions. Such symmetry-inspired modeling facilitates dimensional reduction and numerical tractability. The analysis employs realistic boundary conditions, including convective heat transfer and control of nanoparticle concentration, which are solved numerically using MATLAB’s bvp5c solver. Findings indicate that an increase in activation energy results in a steeper concentration boundary layer under active control, while it flattens in passive scenarios. An increase in the Biot number ($Bi$) and relaxation parameter ($\mathsf{\Gamma }$) enhances heat transfer and thermal response, leading to a rise in temperature distribution in both cases. Additionally, the 3D surface plot illustrates elevation variations from the surface at low inclination angles, narrowing as the angle increases. The Nusselt number demonstrates a contrasting trend, with thermal boundary layer thickness increasing with higher radiation parameters. A graphical illustration of the average values of skin friction, Nusselt number, and Sherwood number for both active and passive scenarios highlights the impact of each case. Under active control, the Brownian motion’s effect diminishes, whereas it intensifies in passive control. Passive techniques, such as zero-flux conditions, offer effective and low-maintenance solutions for systems without external regulation, while active controls, like wall heating and setting a nanoparticle concentration, maximize heat and mass transfer in shear-thinning Carreau fluids. Full article

This study introduces an amphibious spherical robot equipped with a dual-propulsion system (ASR-DPS) and investigates its water-surface motion characteristics. Due to its distinctive spherical geometry, the robot exhibits markedly different hydrodynamic behavior compared to conventional vessels. A comparative analysis of the frontal wetted area is performed, followed by computational fluid dynamics (CFD) simulations to assess water-surface performance. The results indicate that the hemispherical bow increases hydrodynamic resistance and generates large-scale vortex structures as a consequence of intensified flow separation. Although the resistance is higher than that of traditional hulls, the robot’s greater draft and dual-propulsion configuration enhance stability and maneuverability during surface operations. To validate real-world performance, standard maneuvering tests, including circle and zig-zag maneuvers, are conducted to evaluate the effectiveness of the propeller-based propulsion system. The robot achieves a maximum surface speed of 1.2 m/s and a zero turning radius, with a peak yaw rate of 0.54 rad/s under differential thrust. Additionally, experiments on the pendulum-based propulsion system demonstrate a maximum speed of 0.239 m/s with significantly lower energy consumption (220.6 Wh at 60% throttle). A four-degree-of-freedom kinematic and dynamic model is formulated to describe the water-surface motion. To address model uncertainties and external disturbances, two control strategies are proposed: one employing model simplification and the other adaptive control. Simulation results confirm that the adaptive sliding mode controller provides precise surge speed tracking and smooth yaw regulation with near-zero steady-state error, exhibiting superior robustness and reduced chattering compared to the baseline controller. Full article

Modular multilevel converters (MMCs) are widely used in power-conversion applications, including distributed energy storage integration, because of their scalability, high efficiency, and reduced harmonic distortion. Integrating battery storage systems into MMC submodules using dual active bridge (DAB) converters provides electrical isolation and reduces voltage stress, harmonics, and common-mode issues. However, voltage fluctuations due to the battery state of charge can compromise the zero-voltage switching (ZVS) operation of a DAB and increase the reactive power circulation, leading to higher losses and reduced system performance. To address these challenges, this study investigated an active control strategy for submodule voltage regulation in an MMC with DAB-based battery integration. Assuming single-phase-shift modulation, two control strategies were evaluated. The first strategy regulated the DAB voltage on one side to match the battery voltage on the other, scaled by the high-frequency transformer turns ratio, which facilitated the ZVS operation and reduced the reactive power. The second strategy optimized this voltage to minimize the total power-conversion losses. The proposed control strategies improved the efficiency, particularly at low power levels, achieving several percentage points of improvement compared to maintaining a constant voltage. Full article

Dual-active bridge (DAB) converters have emerged as a preferred topology in electric vehicle charging and energy storage applications, owing to their structurally symmetric configuration and intrinsic galvanic isolation capabilities. However, conventional triple-phase shift (TPS) control strategies face significant challenges in maintaining high efficiency across ultra-wide output voltage and load ranges. To exploit the inherent structural symmetry of the DAB topology, a symmetric optimization strategy based on triple-phase shift (SOS-TPS) is proposed. The method specifically targets the forward buck operating mode, where an optimization framework is established to minimize the root mean square (RMS) current of the inductor, thereby addressing both switching and conduction losses. The formulation explicitly incorporates zero-voltage switching (ZVS) constraints and operating mode conditions. By employing the Karush–Kuhn–Tucker (KKT) conditions in conjunction with the Lagrange multiplier method (LMM), the refined control trajectories corresponding to various power levels are analytically derived, enabling efficient modulation across the entire operating range. In the medium-power region, full-switch ZVS is inherently satisfied. In the low-power operation, full-switch ZVS is achieved by introducing a modulation factor λ, and a selection principle for λ is established. For high-power operation, the strategy transitions to a conventional single-phase shift (SPS) modulation. Furthermore, by exploiting the inherent symmetry of the DAB topology, the proposed method reveals the symmetric property of modulation control. The modulation strategy for the forward boost mode can be efficiently derived through a duty cycle and voltage gain mapping, eliminating the need for re-derivation. To validate the effectiveness of the proposed SOS-TPS strategy, a 2.3 kW experimental prototype was developed. The measured results demonstrate that the method ensures ZVS for all switches under the full load range, supports ultra-wide voltage conversion capability, substantially suppresses RMS current, and achieves a maximum efficiency of 97.3%. Full article

Rail transit as a high-energy consumption field urgently requires the adoption of clean energy innovations to reduce energy consumption and accelerate the transition to new energy applications. As an energy-saving fluid machinery, the ejector exhibits significant application potential and academic value within this field. This paper reviewed the recent advances, technical challenges, research hotspots, and future development directions of ejector applications in rail transit, aiming to address gaps in existing reviews. (1) In waste heat recovery, exhaust heat is utilized for propulsion in vehicle ejector refrigeration air conditioning systems, resulting in energy consumption being reduced by 12~17%. (2) In vehicle pneumatic pressure reduction systems, the throttle valve is replaced with an ejector, leading to an output power increase of more than 13% and providing support for zero-emission new energy vehicle applications. (3) In hydrogen supply systems, hydrogen recirculation efficiency exceeding 68.5% is achieved in fuel cells using multi-nozzle ejector technology. (4) Ejector-based active flow control enables precise ± 20 N dynamic pantograph lift adjustment at 300 km/h. However, current research still faces challenges including the tendency toward subcritical mode in fixed geometry ejectors under variable operating conditions, scarcity of application data for global warming potential refrigerants, insufficient stability of hydrogen recycling under wide power output ranges, and thermodynamic irreversibility causing turbulence loss. To address these issues, future efforts should focus on developing dynamic intelligent control technology based on machine learning, designing adjustable nozzles and other structural innovations, optimizing multi-system efficiency through hybrid architectures, and investigating global warming potential refrigerants. These strategies will facilitate the evolution of ejector technology toward greater intelligence and efficiency, thereby supporting the green transformation and energy conservation objectives of rail transit. Full article