We report a fabrication technology for 3D air-core inductors for small footprint and very-high-frequency power conversions.Our process is scalable and highly generic for fabricating inductors with a wide range of geom...We report a fabrication technology for 3D air-core inductors for small footprint and very-high-frequency power conversions.Our process is scalable and highly generic for fabricating inductors with a wide range of geometries and core shapes.We demonstrate spiral,solenoid,and toroidal inductors,a toroidal transformer and inductor with advanced geometries that cannot be produced by wire winding technology.The inductors are embedded in a silicon substrate and consist of through-silicon vias and suspended windings.The inductors fabricated with 20 and 25 turns and 280-350μm heights on 4-16 mm2 footprints have an inductance from 34.2 to 44.6 nH and a quality factor from 10 to 13 at frequencies ranging from 30 to 72 MHz.The air-core inductors show threefold lower parasitic capacitance and up to a 140% higher-quality factor and a 230% higher-operation frequency than silicon-core inductors.A 33 MHz boost converter mounted with an air-core toroidal inductor achieves an efficiency of 68.2%,which is better than converters mounted with a Si-core inductor(64.1%).Our inductors show good thermal cycling stability,and they are mechanically stable after vibration and 2-m-drop tests.展开更多
The casting production process typically involves single jobs and small batches,with multiple constraints in the molding and smelting operations.To address the discrete optimization challenge of casting production sch...The casting production process typically involves single jobs and small batches,with multiple constraints in the molding and smelting operations.To address the discrete optimization challenge of casting production scheduling,this paper presents a multi-objective batch scheduling model for molding and smelting operations on unrelated batch processing machines with incompatible job families and non-identical job sizes.The model aims to minimise the makespan,number of batches,and average vacancy rate of sandboxes.Based on the genetic algorithm,virus optimization algorithm,and two local search strategies,a hybrid algorithm(GA-VOA-BMS)has been designed to solve the model.The GA-VOA-BMS applies a novel Batch First Fit(BFF)heuristic for incompatible job families to improve the quality of the initial population,adopting the batch moving strategy and batch merging strategy to further enhance the quality of the solution and accelerate the convergence of the algorithm.The proposed algorithm was then compared with multi-objective swarm optimization algorithms,namely NSGA-ll,SPEA-l,and PESA-ll,to evaluate its effectiveness.The results of the performance comparison indicate that the proposed algorithm outperforms the others in terms of both qualityand stability.展开更多
基金This project is a part of the TinyPower project,which is funded by the Innovation Foundation(No.67-2014-1).
文摘We report a fabrication technology for 3D air-core inductors for small footprint and very-high-frequency power conversions.Our process is scalable and highly generic for fabricating inductors with a wide range of geometries and core shapes.We demonstrate spiral,solenoid,and toroidal inductors,a toroidal transformer and inductor with advanced geometries that cannot be produced by wire winding technology.The inductors are embedded in a silicon substrate and consist of through-silicon vias and suspended windings.The inductors fabricated with 20 and 25 turns and 280-350μm heights on 4-16 mm2 footprints have an inductance from 34.2 to 44.6 nH and a quality factor from 10 to 13 at frequencies ranging from 30 to 72 MHz.The air-core inductors show threefold lower parasitic capacitance and up to a 140% higher-quality factor and a 230% higher-operation frequency than silicon-core inductors.A 33 MHz boost converter mounted with an air-core toroidal inductor achieves an efficiency of 68.2%,which is better than converters mounted with a Si-core inductor(64.1%).Our inductors show good thermal cycling stability,and they are mechanically stable after vibration and 2-m-drop tests.
文摘The casting production process typically involves single jobs and small batches,with multiple constraints in the molding and smelting operations.To address the discrete optimization challenge of casting production scheduling,this paper presents a multi-objective batch scheduling model for molding and smelting operations on unrelated batch processing machines with incompatible job families and non-identical job sizes.The model aims to minimise the makespan,number of batches,and average vacancy rate of sandboxes.Based on the genetic algorithm,virus optimization algorithm,and two local search strategies,a hybrid algorithm(GA-VOA-BMS)has been designed to solve the model.The GA-VOA-BMS applies a novel Batch First Fit(BFF)heuristic for incompatible job families to improve the quality of the initial population,adopting the batch moving strategy and batch merging strategy to further enhance the quality of the solution and accelerate the convergence of the algorithm.The proposed algorithm was then compared with multi-objective swarm optimization algorithms,namely NSGA-ll,SPEA-l,and PESA-ll,to evaluate its effectiveness.The results of the performance comparison indicate that the proposed algorithm outperforms the others in terms of both qualityand stability.
