Cycle Power Research Articles

Investigation of Power Cycling Degradation on the Dynamic ON-Resistance of HD-GITs

Investigation of Power Cycling Degradation on the Dynamic ON-Resistance of HD-GITs

Prussian Blue-Derived Atomic Fe/Fe3C@N-Doped C Catalysts Supported by Carbon Cloth as Integrated Air Cathode for Flexible Zn-Air Batteries.

The development of an integrated air cathode with superior oxygen reduction reaction (ORR) performance is fundamental to flexible zinc-air batteries (ZABs) for wearable electronics. Herein, a self-assembled metal-organic framework (MOF)-derived strategy is proposed to prepare a atomic Fe/Fe3C@N-doped C catalysts supported by carbon cloth (CC) catalyst for use as an air cathode of flexible ZABs. The Prussian Blue precursor, which self-assembles on the surface of the carbon cloth due to electrostatic attraction, is critical in achieving the uniform dispersion of catalysts with high density loading on carbon cloth substrates. The hollow cubic structure, N-doped carbon layer coating, and the integrated electrode design can provide more accessible active sites and facilitate a rapid electron transfer and mass transport. Density functional theory (DFT) calculation reveals that the electronic interactions between the Fe-N4 and Fe3C dual active sites can optimize the adsorption-desorption behavior of oxygen intermediates formed during the ORR. Consequently, the Fe/Fe3C@N-doped C/CC exhibits an excellent half wave potential (E1/2 = 0.903V) and superior long-term cycling stability in alkaline environments. With excellent ORR performance, ZABs and flexible ZABs based on Fe/Fe3C@N-doped C/CC air cathode demonstrate excellent overall electrochemical performance in terms of open circuit voltage, maximum power density, flexibility, and cycling stability.

Influence of different vibration directions on the solder layer fatigue in IGBT modules

Insulated-gate bipolar transistor (IGBT) modules are extensively utilized in high-speed trains, ships, and electric vehicles. Compared to those used in power systems, IGBT modules in these applications are more susceptible to vibration effects on their reliability. This paper proposes a multi-physics field simulation method and a lifetime model for IGBT modules to assess the impact of different vibration directions on solder layer fatigue. Initially, a multi-physics field model of the IGBT module is developed, incorporating electrical, thermal, mechanical, and vibration coupling. The effectiveness of this multi-physics simulation model is verified by an experimental platform. Subsequently, the influence of different vibration directions on solder layer fatigue in the IGBT module is analysed, and a life model of the IGBT is proposed through simulation. Finally, a power cycling with a vibration environment experimental platform is established to validate the effect of vibration on solder layer fatigue in the IGBT module. The simulation and experimental results indicate that vertical vibration accelerates the solder layer fatigue of IGBT modules, and the lifetime of an IGBT module operating under vertical vibration at 30 Hz is about 15 % shorter than that of an IGBT module operating under power cycling alone. The error between the calculated results of the solder layer failure and the experimental result is <5 %.

Part-load performance analysis of a modular biomass boiler with a combined heat and power industrial Rankine cycle and supplementary sCO2 Brayton cycle

Abstract The addition of a supplementary high efficiency cycle integrated with an existing steam power cycle may increase energy efficiency and net generation. In this paper, part load performance and operation of a modular biomass boiler with an existing industrial Rankine steam heat and power cycle and supplementary supercritical CO2 (sCO2) Brayton cycle is analysed. The aim is to leverage the high efficiency of the sCO2 cycle by retrofitting sCO2 heaters in the existing biomass boiler, increasing net power output and thermal efficiency. With nominal load performance previously investigated, understanding part-load performance and operation is vital to determine cycle feasibility. A quasi-steady-state one dimensional thermofluid network model was used to simulate the integrated cycle performance for loads ranging from 100% to 60%. The model solves the mass, energy, momentum, and species balance equations, capturing detailed component characteristics. Two control methodologies are explored for the sCO2 Brayton cycle, namely inventory control and inventory control combined with throttling valve control. Inventory control is selected as the better performing control strategy for load following, maintaining high thermal efficiency across partial loads. At 60% load, the sCO2 compressor operates near the pseudo-critical point, leading to a sharp decrease in sCO2 cycle capacity, which requires careful management of inventory control. Two sCO2 heater configurations are investigated, namely a single convective-dominant heater, and a dual heater configuration with a radiative and a convective heater. The single heater configuration is preferred to minimise adverse impacts on the Rankine cycle superheaters.

Comparison of Lower-Limb Muscle Synergies Between Young and Old People During Cycling Based on Electromyography Sensors—A Preliminary Cross-Sectional Study

The purpose of this study was to analyze the lower-limb muscle synergies of young and older adults during stationary cycling across various mechanical conditions to reveal adaptive strategies employed by the elderly to address various common pedaling tasks and function degradation. By comparing lower-limb muscle synergies during stationary cycling between young and old people, this study examined changes in muscle synergy patterns during exercise in older individuals. This is crucial for understanding neuromuscular degeneration and changes in movement patterns in older individuals. Sixteen young and sixteen older experienced cyclists were recruited to perform stationary cycling tasks at two levels of power (60 and 100 W) and three cadences (40, 60, and 90 rpm) in random order. The lower-limb muscle synergies and their inter- and intra-individual variability were analyzed. Three synergies were extracted in this study under all riding conditions in both groups while satisfying overall variance accounted for (VAF) &gt; 85% and muscle VAF &gt; 75%. The older adults exhibited lower variability in synergy vector two and a higher trend in the variability of activation coefficient three, as determined by calculating the variance ratio. Further analyses of muscle synergy structures revealed increased weighting in major contribution muscles, the forward-shifting peak activation in synergy one, and lower peak magnitude in synergy three among older adults. To produce the same cycling power and cadence as younger individuals, older adults make adaptive adjustments in muscle control—increased weighting in major contribution muscles, greater consistency in the use of primary force-producing synergies, and earlier peak activation of subsequent synergy.

CoFe2O4 with the In-Situ Formed Oxygen Vacancies and Co Particles as an Efficient Bifunctional Catalyst for Rechargeable Zinc-Air Batteries.

Rechargeable zinc-air batteries (RZABs) are considered as one of the most promising clean energy device due to their abundant resources, low cost and environmental friendliness. However, their energy efficiency and cycle life are far from satisfactory due to the poor activity and stability of bi-functional electrocatalyst in air cathode. In this work, an efficient bi-functional catalyst (rGO-CoFe2O4/Co) was derived from its precursor (rGO-CoFe2O4) through a simple annealing process. Electrochemical measurements prove that rGO-CoFe2O4/Co with the in-situ formed Co nano particles and rich oxygen vacancies appears excellent oxygen reduction reaction and oxygen evolution reaction catalytic activity compared to its counterpart. Its half-wave potential is 0.81 V (vs RHE) and the OER overpotential is only 310 mV (vs RHE). In addition, rechargeable zinc-air batteries assembled with rGO-CoFe2O4/Co show the highest peak power density (128.9 mW cm-2) and cycling stability compared to rGO-CoFe2O4 and commercial Pt/C-RuO2 catalysts. This work provides a simple strategy for the design of advanced bifunctional catalysts.

Numerical Modelling Of A Primary Heat Exchanger in sCO2 Power Cycles for Thermal Energy Storage Systems

Abstract Renewable energy sources are the key for long-term decarbonization of energy. However, the intermittent nature of renewables does not always meet the energy demand in the electrical grid. Thus, electrical heated Thermal Energy Storage systems (TES) coupled with sCO2 power cycles are investigated at Helmholtz-Zentrum Dresden-Rossendorf as a possible solution to balance this mismatch. In this study, a Printed Circuit Heat Exchanger (PCHE) is considered as candidate for the 1 MW primary heat exchanger, given the mechanical challenge induced by drastic pressure difference between the hot fluid of the TES and the cold fluid of the power cycle. The present work consists of two parts, one elaborates a 1D model in order to optimize the PCHE regarding the pump power required to compensate the pressure loss. It was found that the hot fluid coming from the TES accounts for 80 % of the total pump power after optimization because of its low density and its high mass flow rate. Furthermore, 3D simulations by Computational Fluid Dynamics (CFD) were done and compared to the results from the 1D model to ensure its validity. It was observed that the results from the 1D model and the CFD simulations are consistent, with a slight potential deviation in the calculation of the pressure profile.

Change in sprint cycling torque is not associated with change in isometric force following six weeks of sprint cycling and resistance training in strength-trained novice cyclists.

Strong relationships exist between sprint cycling torque and isometric mid-thigh pull (IMTP) force production at one timepoint; however, the relationships between the changes in these measures following a training period are not well understood. Accordingly, this study examined the relationships in the changes of sprint cycling torque and IMTP force following six-weeks of sprint cycling and resistance training performed by strength-trained novice cyclists (n=14). Cycling power, cadence, torque and IMTP force (Peak force [PF]/torque, average and peak rate of force/torque development [RFD/RTD], and RFD/RTD from 0 to 100ms and 0-200ms) were assessed before and after training. Training consisted of three resistance and three sprint cycling sessions per week. Training resulted in improvements in IMTP PF (13.1%) andRFD measures (23.7%-32.5%), cycling absolute (10.7%) and relative (10.5%) peak power, peak torque (11.7%) and RTD measures (27.9%-56.7%). Strong-to-very strong relationships were observed between cycling torque and IMTP force measures pre- (r=0.57-0.84; p<0.05) and post-training (r=0.63-0.87; p<0.05), but no relationship (p>0.05) existed between training-induced changes in cycling torque and IMTP force. Divergent training-induced changes in sprint cycling torque and IMTP force indicate that these measures assess distinct neuromuscular attributes. Training-induced changes in IMTP force are not indicative of training-induced changes in sprint cycling torque.

Optimization of a Biomass-Based Power and Fresh Water-Generation System by Machine Learning Using Thermoeconomic Assessment

Biomass is a viable and accessible source of energy that can help address the problem of energy shortages in rural and remote areas. Another important issue for societies today is the lack of clean water, especially in places with high populations and low rainfall. To address both of these concerns, a sustainable biomass-fueled power cycle integrated with a double-stage reverse osmosis water-desalination unit has been designed. The double-stage reverse osmosis system is provided by the 20% of generated power from the bottoming cycles and this allocation can be altered based on the needs for freshwater or power. This system is assessed from energy, exergy, thermoeconomic, and environmental perspectives, and two distinct multi-objective optimization scenarios are applied featuring various objective functions. The considered parameters for this assessment are gas turbine inlet temperature, compressor’s pressure ratio, and cold end temperature differences in heat exchangers 2 and 3. In the first optimization scenario, considering the pollution index, the total unit cost of exergy products, and exergy efficiency as objective functions, the optimal values are, respectively, identified as 0.7644 kg/kWh, 32.7 USD/GJ, and 44%. Conversely, in the second optimization scenario, featuring the emission index, total unit cost of exergy products, and output net power as objective functions, the optimal values are 0.7684 kg/kWh, 27.82 USD/GJ, and 2615.9 kW.

Semi-Closed Oxy-Combustion Combined Cycles for Combined Heat and Power Applications

Abstract This study focuses on the design and comparison of three utility-scale combined heat and power (CHP) cycles with carbon capture and storage (CCS): (i) a CHP semi-closed oxy-combustion combined cycle (SCOC-CC), (ii) a CHP natural gas combined cycle (NGCC) with postcombustion CCS, and (iii) a CHP NGCC with postcombustion CCS and supplementary firing. Performance evaluations are conducted at the design point and partial load (gas turbine at 30%) for different exports of high-temperature pressurized steam. The comparison is extended against two reference separate production systems with CCS, one based on postcombustion technologies, and another based on oxy-combustion. Simulations of the H-class gas turbines are performed using gas steam (GS), a specific in-house validated software, while the heat recovery steam cycle is modeled using Thermoflex. The CO2 capture processes employ validated models in Aspen Plus. The results highlight the suitability of the SCOC-CC for CHP applications, demonstrating superior performance and flexibility compared to CHP postcombustion technologies at both nominal and minimum loads. The SCOC cycle achieves a maximum first-law efficiency of 65.95%, outperforming CCS technologies that generate electricity and heat separately and enabling fuel savings up to 9.2%.

Revealing interfacial degradation of Bi2Te3-based micro thermoelectric device under current shocks

Micro thermoelectric devices (micro-TEDs) offer great potential for IoT and electronic thermal management. However, they face challenges with reliability under high current densities. This study elucidates the failure mechanisms of Bi2Te3-based micro-TEDs subjected to current shocks. Experimental results indicate that at a high current density of 1800 A/cm2, the internal resistance of micro-TEDs increased by 12.9 % to 2.034 Ω. This led to a 52.0 % decrease in maximum output power at a 20 K temperature difference, dropping to 1.53 mW. Additionally, as the frequency of ON/OFF current applied to micro-TED increases, the resistance growth rate jumped from 0.764 mΩ/h for slow power cycling to 2.328 mΩ/h for fast power cycling. This indicates that higher cycling frequencies exacerbate the degradation of the device. In-situ TEM analysis revealed that current-induced elemental diffusion and electrical stress release led to the formation of NiTe2 nanoparticles and intergranular fractures within the Bi2Te3 materials. These results indicate that interfacial degradation and subsequent grain delamination are primary causes to micro-TED failure under current shocks. These findings underscore the significance of considering electrical stress in micro-TED design to enhance reliability and performance for high-power applications.

Energy, exergy and exergoeconomic analyses and ANN-based three-objective optimization of a supercritical CO2 recompression Brayton cycle driven by a high-temperature geothermal reservoir

The use of CO2-based power cycles to harness high-temperature geothermal resources is an interesting application that has been little explored. Therefore, to obtain a more holistic understanding of these systems, in this work, a supercritical CO2 recompression Brayton cycle is assessed. For comparison, the performances of a recuperative cycle and a recompression cycle with intercooling were also computed. Detailed mathematical models were developed and then, artificial neural network-based surrogate models were adopted to conduct multi-objective optimization. Results of the baseline simulations show that, the high temperature recuperator and the turbine are the most important components from both exergy and exergoeconomic approaches. The optimizations reveal that the intercooled cycle is superior to the other layouts in all the cases while the recuperative cycle is not feasible with reinjection temperatures greater or equal to 150 °C. When the reinjection temperature is constrained to 150 °C, the intercooled cycle attains 4472.70 kW, 62.10 % and 14.42 $/GJ for net power, exergy efficiency and product unit cost, respectively, whereas without this constraint, it achieves 5394.09 kW, 61.83 %, 11.79 $/GJ. In conclusion, the adoption of advanced layouts of the CO2 cycle is beneficial for this application from both technical and economic points of view.

Solar cells combined with geothermal or wind power systems reduces climate and environmental impact

This research investigates the environmental sustainability of three integrated power cycles: combined geothermal-wind, combined solar-geothermal, and combined solar-wind. Here, a promising solar technology, the perovskite solar cell, is considered and analysed in conjunction with another renewable-based cycle, evaluating 17 scenarios focusing on improving the efficiency and lifespan. Among the base cases, combined solar-wind had the lowest ozone depletion impact, while combined geothermal-wind had the lowest freshwater ecotoxicity and marine ecotoxicity impacts. The study shows that extending the perovskite solar cell lifespan from 3 to 15 years reduces CO2 emissions by 28% for the combined solar-geothermal and 56% for the combined solar-wind scenario. The most sustainable cases in ozone depletion, marine ecotoxicity, freshwater ecotoxicity, and climate change impacts are combined solar-wind, combined solar-geothermal, and combined geothermal-wind, respectively, among all evaluated scenarios. This research suggests investing in the best mix of integrated power cycles using established and emerging renewable technologies for maximum environmental sustainability.

Reliability Simulation of IGBT Module with Different Solders Based on the Finite Element Method

The interconnecting solder is a key control factor for the reliability of electronic power packaging because it highly affects the junction temperature of insulated-gate bipolar transistor (IGBT) modules and is prone to plasticity, creep, and other failure behaviors under temperature-change environments. In this paper, the interconnecting performance and fatigue life of five different kinds of solders such as SAC305, sintered silver, Au80Sn20, sintered copper, and pure In under direct current (DC), power cycle, and electro-thermal coupling complex environments were studied based on electro-thermal multi-physical field coupling finite element simulation method, respectively. Results show that the sintered silver owns the most outstanding thermal reliability and the DC operating junction temperature of the IGBT module after utilizing sintered silver solder is only 90.2 °C, which is nearly 15 °C lower than that of the IGBT module utilizing SAC305 solder. Furthermore, in the power cycle reliability test, the fatigue life of Au80Sn20 solder reaches a maximum of 3.26 × 107 cycles while the life of indium presents only 5.85 × 103 cycles, a difference of nearly four orders of magnitude. Finally, under the complex environment of electro-thermal coupling, the fatigue life of Au80Sn20 solder is also the largest at 1.9 × 106 cycles, while the smallest life of solder becomes SAC305 solder at 4.44 × 102 cycles. The results of this paper can provide a theoretical basis for solder selection and life prediction of the IGBT module, which is of great significance in improving the reliability of power electronic packaging.

Collaborative Training of Data-Driven Remaining Useful Life Prediction Models Using Federated Learning

Remaining useful life prediction models are a central aspect of developing modern and capable prognostics and health management systems. Recently, such models are increasingly data-driven and based on various machine learning techniques, in particular deep neural networks. Such models are notoriously “data hungry”, i.e., to get adequate performance of such models, a substantial amount of diverse training data is needed. However, in several domains in which one would like to deploy data-driven remaining useful life models, there is a lack of data or data are distributed among several actors. Often these actors, for various reasons, cannot share data among themselves. In this paper a method for collaborative training of remaining useful life models based on federated learning is presented. In this setting, actors do not need to share locally held secret data, only model updates. Model updates are aggregated by a central server, and subsequently sent back to each of the clients, until convergence. There are numerous strategies for aggregating clients’ model updates and in this paper two strategies will be explored: 1) federated averaging and 2) federated learning with personalization layers. Federated averaging is the common baseline federated learning strategy where the clients’ models are averaged by the central server to update the global model. Federated averaging has been shown to have a limited ability to deal with non-identically and independently distributed data. To mitigate this problem, federated learning with personalization layers, a strategy similar to federated averaging but where each client is allowed to append custom layers to their local model, is explored. The two federated learning strategies will be evaluated on two datasets: 1) run-to-failure trajectories from power cycling of silicon-carbide metal-oxide semiconductor field-effect transistors, and 2) C-MAPSS, a well-known simulated dataset of turbofan jet engines. Two neural network model architectures commonly used in remaining useful life prediction, long short-term memory with multi-layer perceptron feature extractors, and convolutional gated recurrent unit, will be used for the evaluation. It is shown that similar or better performance is achieved when using federated learning compared to when the model is only trained on local data.

Investigating the impact of nanofluids and exergy metrics for integrated solar-biomass SCO2 power and desalination cycles

Several strategies have emerged for utilizing waste heat across diverse sectors. Yet, integrated systems that merge power generation with freshwater production, especially those leveraging renewable energy, remain relatively unexplored. Addressing this gap, a novel solar biomass-driven system is under development for power generation and desalination facilities. In the suggested system, rather than wasting the energy of a supercritical CO2 power cycle, a bottoming cycle is proposed to augment energy utilization factor (EUF). By integrating humidification-dehumidification, thermal vapor compression, and reverse osmosis (HDH-TVC-RO) with a multi-effect distillation (MED) unit, freshwater production rate is significantly enhanced. The outcomes reveal a freshwater output of 29.36 kg/s, a gained output ratio (GOR) of 17.36, and the EUF of 3.372. Various nanofluids have been assessed for the solar collector and due to superior total exergy efficiency and less corrosion effects, Cu- and carbon-based nanoparticles are recommended. Sensitivity analysis indicates that increasing the pressure ratio of compressors boosts the total GOR. Furthermore, adjustments to both the parameters of pressure of steam fed to HDH-TVC, and the compressor pressure ratio demonstrate a linear effect on EUF behaviour.

Opportunities to Enhance sCO2 Power Cycle Turbomachinery with Bearingless Motor/Generators

Thermal power cycles using sCO2 as a working fluid place extreme demands on their turbomachinery components and their electric motors/generators. In this paper, new system topologies for sCO2 turbomachinery are proposed which take advantage of “bearingless” electric machine technology to improve performance. Bearingless motors/generators are a new type of electric machine which integrate the functionality of active magnetic bearings into the existing hardware of an electric motor/generator. The existing electromagnetic surfaces and materials are reused to enable controllable production of radial forces on the machine shaft. This is envisioned to improve hermetic direct-drive turbomachinery systems by either augmenting existing bearings (i.e., bearing assist) or replacing existing bearings (i.e., bearing removal). The state-of-the-art technologies for several bearing types (gas foil bearings, externally pressurized porous (EPP) gas bearings, and active magnetic bearings) and electric machines are reviewed to motivate the introduction of bearingless technology. Two system designs using bearingless machines are proposed and compared against existing commercial solutions in terms of maximum shaft weight, number of passthroughs into the hermetic environment, cost, and complexity. A case-study bearingless motor/generator is assessed via simulations and a hardware prototype to investigate practical considerations for using bearingless technology in sCO2 turbomachinery. The proposed bearingless solutions have potential to enable a new generation of sCO2 turbomachinery with improved reliability, reduced complexity, and lower cost. This paper shows that by transforming the motor/generator already present in turbomachinery into a bearingless motor/generator, the technical challenges involved with sCO2 can be overcome without adding significant cost.

Failure Mechanism Analysis of 1.2 kV SiC MOSFETs Under Low-Temperature Storage, Power Cycling, and Short-Circuit Interactions

Failure Mechanism Analysis of 1.2 kV SiC MOSFETs Under Low-Temperature Storage, Power Cycling, and Short-Circuit Interactions

Optimizing Concentrated Solar Power: High‐Temperature Molten Salt Thermal Energy Storage for Enhanced Efficiency

ABSTRACTMolten salts (MSs) thermal energy storage (TES) enables dispatchable solar energy in concentrated solar power (CSP) solar tower plants. CSP plants with TES can store excess thermal energy during periods of high solar radiation and release it when sunlight is unavailable, such as during cloudy periods or at night. This capability allows these plants to provide reliable, dispatchable power, ensuring a continuous electricity supply to the grid. This paper examines the challenges and opportunities of utilizing higher‐temperature molten salt formulations to enhance power cycle efficiency. Drawing on existing literature, performance analysis of existing power plants, and novel simulation results, we project the expected technological improvements by the end of this decade. By using 15 h of TES and a higher temperature MS formulation, with heat transfer fluid hot temperatures of 700°C, and a power cycle 350 bar 700°C of efficiency 48%, the annual electricity production from a 115 MW power plant in Daggett, California is 688 GWh, the total installed cost is $684 m while the 25‐year LCOE is 6.37 c/kWh.

A new system using refuse-derived fuel as a feedstock for hydrogen and power co-generation: A techno-environmental assessment

Refuse-derived fuel (RDF) offers a promising opportunity for Canada to proceed with its transition towards a circular economy. This study focuses on the development of a pseudo-steady-state process simulation model to integrate RDF processing and utilization technologies with the existing plants. Canada’s RDF is chosen as a potential feedstock and is coupled with the two cycles, namely Sulfure Iodine (S-I) thermochemical cycle for hydrogen production and dual pressure loop power (DPLP) cycle for electricity generation. A comprehensive process modeling and simulation is undertaken in the Aspen Plus software package. An integrated environmental and thermodynamic assessment of the plant, including energy and exergy analyses, is conducted. Several sensitivity analyses are conducted to predict the ideal operational parameters for optimized efficiency. It is found that a feed of 1300 kg/h RDF generates 96.76 kg of clean hydrogen and 382.24 kW of clean power. The results show RDF-to-power and RDF-to-H2 energy efficiency of 22.19 % and 25.27 % respectively. Regarding the environmental performance, the results show that the proposed plant avoids 423.82 tons of CO2 emissions per year for clean hydrogen production and 1685.45 tons of CO2 emissions per year for clean power production. The overall performance of the developed system in terms of efficiencies is 35.91 % for energy and 42.46 % for exergy.