Power Matching Research Articles

Research on Shovel-Force Prediction and Power-Matching Optimization of a Large-Tonnage Electric Wheel Loader

Nowadays, rapid development has been achieved with respect to the electric wheel loader (EWL). The operational efficiency of EWLs is affected by many factors; especially, shovel force is a very important factor. For large-tonnage EWLs, when employing empirical, formula-based methods to predict shovel force, the generated errors are significant, with errors frequently reaching levels of up to 30%. To solve this problem, a method, based on the discrete element method (DEM), to predict shovel force is put forward in this paper. The material parameters are calibrated by a backpropagation (BP) neural network learning algorithm (NNLA). The material model is inputted into multi-body-dynamics software. A simulation model to accurately predict the shovel force is created. The error between the test results and the simulation results is 7.8%, demonstrating a high level of consistency. To validate the reliability of this method, the 35-ton EWL is taken as an example for research, and the straight-line driving test and the power-matching test are conducted. While ensuring the operational efficiency of the EWLs, the power loss is also a crucial consideration. The drastic changes in shovel force often result in front-tire slippage of the EWLs. To minimize wheel slippage during the shoveling section, the matching of the electric motor was optimized. In summary, material parameters were calibrated using a combined method of BP NNLA to predicate shovel force of a large-tonnage EWL. Additionally, the power matching of the EWL has been optimized to accord with the shoveling section of the device.

Formulating an optimization algorithm for optimal planning and assessment of rule-based hybrid load following micro-combined heat and power systems

This manuscript presents a logical-based method with a constrained programming approach for making use of the principle. The proposed optimal approach is the improved chameleon swarm algorithm (ICSA). The navigating and hunting behavior of CSA is improved with the crossover and mutation processes, and it is defined as the ICSA approach. The proposed hybrid approach is the number one power consumption, greenhouse gas, and total annual cost (TAC), in addition to including conditions largely based entirely on the monitoring approach, which is a mixture of those standards. These three power-corresponding parameters have been exploited to examine the overall performance of every method corresponding to the absorbed power providers employing the construction call for requests. The calculation of the established effectiveness for four varieties of residents’ homes suggests the not-infrequent place hybrid method. This increases the exploitation of the cogeneration system as well as the proposed method because the most appropriate techniques include measures capable of obtaining excellent conciliation answers done with TAC at 55%, primary energy consumption (PEC) at 14%, and greenhouse generation (GHG) at 9% discounts correspondingly. However, the proposed method obtains optimum discounts in TAC and optimum overall performance for power matching by utilizing identical boundaries for GHG and PEC in assessment to the always infrequent place hybrid technique. The prey-in cost for energy era with nearly 60 in TAC is perceived as the maximum leading monetary constraint for sensibility evaluation when micro-cogeneration units use over 3% gain and are the most disrupted outcome for randomly evaluated.

A S-band switchless bi-directional transceiver with a 52% fractional bandwidth in CMOS technology

This paper presents a bi-directional switchless wideband transceiver front-end for S-band multi-functional digital array system. In an S-band digital array system, a silicon-based RF front-end module requires a high integration level, compact size, large bandwidth, and low power consumption features. A bi-directional switchless transceiver could provide a compact solution. However, the shared RF matching network in such a transceiver is crucial due to its influence on Rx sensitivity, Tx output power, TRx isolation, and bandwidth. This work proposes a compact π matching network for simultaneous broadband Rx noise matching, Tx power matching, and TRx isolation. Also, a double quadrature down-conversion architecture is proposed to improve image signal rejection in the whole S-band. Therefore, false detection in the S-band digital array can be avoided. Fabricated in a 0.18μm CMOS technology, this S-band transceiver occupies a silicon area of 3.2 × 2 mm2. In the Rx mode, the measured gain is 20.7–28 dB in 2–4 GHz at 25 °C. The RX noise figure is 9.5–11.5 dB, and the input 1-dB compression point is -11 dBm. In the Tx mode, the gain is 16.5–19.6 dB in 2–4 GHz at 25 °C, and Psat is 10.2 dBm. The RX bandwidth is 2–3.4 GHz, while that of Tx is 2–4 GHz. The corresponding fractional bandwidth is 52% and 67%, respectively. Furthermore, this transceiver shows an image rejection ratio of 28.9–41.4 dB suppression at the operation frequency band.

Teaching building towards carbon neutrality: Power matching and economy of source-grid-load-storage system

Teaching building towards carbon neutrality: Power matching and economy of source-grid-load-storage system

Numerical study on spray cooling of aircraft equipment cabin

With the increase in the number of aircraft onboard equipment and the sharp increase in heat dissipation power, the thermal control of cabin equipment has become one of the important issues restricting the development of high-speed aircraft technology. Spray cooling has the advantages of high cooling efficiency, simple cooling system structure, easy adjustment and control, etc. It is one of the most effective methods for thermal control of the aircraft equipment cabin. This work builds a simplified physical model of the aircraft equipment cabin, and improves the simulation method of the spray cooling of the equipment cabin. To test the accuracy of the simulation method, an experimental validation study was carried out. In the three-dimensional numerical simulation of cabin spray cooling, the structure characteristics of multi-nozzle spray droplet field, temperature field and flow field are addressed. It’s found that using multi-nozzle spray cooling for large-area and multi-surface equipment cabins is feasible, which can effectively control the temperature of most surfaces. However, for some slit areas, such as between adjacent equipment and between the equipment and the cabin, the temperature is relatively high due to the ineffective coverage of spray cooling. An improved method was applied to investigate the variation of temperature and pressure of the cabin during spray cooling. The study found that the pressure in the cabin can be flexibly controlled by adjusting the size of the exhaust hole of the cabin. The matching of the heating power of the cabin and the spray cooling capacity is an important guarantee condition for realizing the temperature and pressure control of the cabin. This study provides valuable reference data for engineers to design aircraft cabin cooling schemes.

Do we love celebrity endorsers? The joint impacts of consumers' need for status, celebrity’s star power and image congruence on celebrity endorsement effectiveness

PurposeThe current study aims to examine the joint impact of consumers' need for status (NFS), celebrity's star power and consumer-celebrity image match on consumers' attitudes toward the celebrity endorsement.Design/methodology/approachA factorial design was employed to test the research model. Consumer-celebrity image match was manipulated, and consumers' NFS and celebrity's star power was captured using existing measurement scales. A total of 365 responses were collected via Qualtrics. Hayes's (2013) PROCESS procedure was used to analyze the data and test hypotheses.FindingsResults indicate that consumers with high (vs low) NFS have more favorable attitudes toward the endorsed brand. More importantly, consumers high in NFS, in an endorsement where celebrity-consumer image matches, have more favorable attitudes toward the brand endorsed by a celebrity with more (vs less) star power. In contrast, in an endorsement where celebrity-consumer image mismatches, they react the same regardless of the endorser's star power.Practical implicationsThis study offers suggestions to hospitality marketing professionals in strategically using celebrity endorsers in their marketing campaigns and strategies that allows firms to further formulate positive and enduring brand images while encouraging favorable consumer behaviors.Originality/valueWhile most hospitality studies have focused on the traits of celebrity endorsers, little attention has been paid to the impact of consumers' characteristics on celebrity endorsement. This study advances the growing literature on hospitality celebrity endorsement by providing empirical evidence to delineate the relationship among celebrities, endorsed brands and consumers.

The Scheme of Movable DC Ice Melting Device Based on the Engine-Generator Topology

In this article, an entire scheme of DC ice-melting devices based on the engine-generator topology is proposed to solve the problem of poor portability caused by the current devices. It is found that the engine-generator topology suffers from a power mismatch when starting with load, which may eventually lead to starting failure. A soft-start strategy is proposed to control the power required by the load by controlling the duty cycle of the switching tube to achieve real-time power matching. Compared with the most popular phase-controlled rectifier DC ice melting device, the entire scheme of the device is proposed, which not only achieves continuous voltage and current adjustment but also effectively reduces the ripple of the output and control complexity. The feasibility of the proposed soft-start strategy and the entire scheme of the device is verified by simulation results.

Research on hybrid power load matching control method of new energy pumping machine

In order to improve the energy saving effect of new energy pumping machine, the power matching energy saving control of wind energy, electric energy and pumping machine load should be carried out when the actual wind speed is lower than the rated wind speed of the system. In this paper, according to the wind power hybrid transmission system, we study the load matching energy saving control strategy and method that takes into account the simultaneous change of wind speed and load, and propose the hybrid power load matching adaptive energy saving control strategy based on the cascade controller. In the strategy, the motor torque control method is used to eliminate the pressure deviation and realize the system pressure tracking load matching adaptive control, while keeping the motor output torque stable.

Thermodynamic analysis and comprehensive system optimization of the near zero emission hybrid power based on SOFC-ICE integrated system fueled with ammonia

The highly efficient heat and mass integrations fueled with ammonia of solid oxide fuel cell and reciprocating piston internal combustion engine are conducted from the viewpoints of characters of restrained / unrestrained chemical reaction and principle of energy cascade utilization. According to previous studies, we classified such integrations into serial and parallel topologies. Based on the detailed and verified models, the power matching limits of serial and parallel integrations are proposed first, showing a narrow scale of power matching of fuel cell and engines, due to the finite engine displacement. Furthermore, based on the design concepts of serial and parallel integrations, the improvement and optimization of combined systems were conducted, which showed that the possibly highest efficiency of serial and parallel systems can reach 70.53% and 68.40%, respectively. Additionally, the exergy analysis of systems could prove that such heat and mass integrations can effectively use remaining heats and fuels, leading to less exergy destructions and optimal designs and operation points achievement, while the maximum exergy destruction occurs at engine. Finally, the environmental analysis results showed that the corrected NO, NO2, N2O and NH3 emissions can reach 0.01 mg/kWh, 5.00 μg/kWh, 29.50 mg/kWh and <5 ppm, achieving near zero emissions.

Adaptive Coordination Control Based on Alkaline Water Electrolyzers and Battery Driven by Wind Power

With the widespread use of clean energy sources, there has been a growing interest in obtaining green and pure hydrogen from wind power. However, wind energy is characterized by randomness and volatility, which results in a low grid connection rate for wind turbines and makes it difficult to integrate wind energy into the power grid. In this context, this article proposes an adaptive coordinated control strategy considering the wind turbine, alkaline electrolyzer, battery, and local loads. Using the DC bus voltage as the connecting signal, adaptive power control and voltage control methods are developed for the wind turbine, energy storage battery, and electrolyzer to achieve power matching in the system. Finally, the proposed research results are validated through Matlab/Simulink simulation module.

Digital Control Method and Performance Analysis of the Double-Compound Axial Piston Pump.

The flow control range of the double-compound axial piston pump with the traditional mechanical-hydraulic feedback servo control is limited and the accuracy is poor. Accordingly, this paper proposes a digital control scheme and its control strategy using a linear stepper motor direct drive servo valve for the precise control and double pumps cooperation of the double-compound axial piston pump. A numerical model of the digital control double-compound axial piston pump is established, and the validity of the model is verified by experimental tests. The performance advantages of the digital control method relative to the mechanical-hydraulic feedback servo control method are analyzed, as is the performance of the control strategy for double pumps. The results show that the digital control method can achieve a wider range of flow control than the traditional mechanical-hydraulic feedback servo control method and avoid the torque impact on the prime mover caused by the active control. The combination of the flow control and the power control including four control modes can meet the performance requirements of the double-compound axial piston pump. The highest priority is given to the energy-saving control, which can reduce the displacement of the main pump in the nonworking state to reduce the additional power loss. The study provides a basis for the accurate matching and optimization of power to load and flow to operating speed of the double-compound axial piston pump.

Forecasting Regional Energy Consumption via Jellyfish Search-Optimized Convolutional-Based Deep Learning

The energy sector must achieve a delicate balance between energy supply and demand. Highly accurate energy consumption forecasts can help plant operators achieve this goal. In this study, various techniques from three artificial intelligence categories, namely, convolutional neural networks (CNNs), machine learning (ML), and time-series deep learning (DL), were applied to predict short-term regional energy consumption from a power company. An image conversion process was proposed to utilize the powerful image-processing capabilities of CNNs, in which numerical matrices of input values created by the sliding-window technique are encoded into two-dimensional grayscale images as input for CNN models. The proposed method outperformed conventional numerical input methods. Then, the best ML and time-series DL models were combined into ensemble models with ImageNet-winning CNN architectures based on the rationale of utilizing the strengths of each approach and compensating for their limitations. However, according to the numerical experiments for the regional energy consumption prediction, the ensemble models had lower performance than CNNs alone. Various leading models performing single-step or multistep forecasting and models that use seasonal or annual data were constructed. The performance of all the constructed models was evaluated, and the most efficient models were determined as proposed models. Finally, a nature-inspired optimization algorithm, Jellyfish Search (JS), was used to fine-tune the proposed models’ hyperparameters to minimize prediction error. The results revealed that the fine-tuning of hyperparameters via the JS algorithm significantly enhanced the precision of the CNN models, resulting in a mean absolute percentage error (MAPE) improvement range of 4.4% to 17.5% compared to the default models. The proposed models can help utilities plan daily power allocation and match supply and demand to maintain a stable power system.

An Electric Vehicle Charging Method Considering Multiple Power Exchange Modes’ Coordination

To achieve sustainable environmental development, numerous countries and governments have been vigorously promoting the proliferation of electric vehicles (EVs) through a series of policy measures and economic subsidies. With the increasing number of EVs, multiple EV charging modes are being researched to satisfy owners’ requirements. In this paper, an EV charging method considering multiple power exchange modes’ coordination is proposed for meeting owners’ requirements with cost-effectiveness. In the proposed method, the battery swapping (BS) station, building-to-vehicle (B2V) station, and grid-to-vehicle (G2V) station are considered. In G2V stations, EVs charge from the power grid. In B2V stations, distributed renewable energy generation is considered as the energy provider. This study contemplates the use of photovoltaic power systems in B2V stations for the charging of EVs. In BS stations, the power exchange among batteries and the power grid is considered. The battery energy storage is utilized for reducing the battery degradation cost (BDC) and power cost. EVs are dispatched to the corresponding charging stations according to the electric price, BDC, and so on. In the dispatching process, the particle swarm optimization (PSO) algorithm and Hungarian algorithm are applied. Several case studies are presented to validate the effectiveness of the proposed method and the power matching between EVs and charging modes is discussed.

Design of large-angle distortion-free and spot adjustable LED spot array projector based on microlens array and eyepiece

The spot array projector has long been a challenging and intriguing research focus in the fields of projection and lighting applications. In the current literature, there is a lack of a comprehensive and detailed presentation on the design and analysis method for a spot array generator based on the structure of imaging eyepiece and MLA. We present a novel design and optimization method for a large-angle, distortion-free and spot adjustable LED spot array projector that is composed of an eyepiece, two microlens arrays (MLAs), and a micro-LED array (MLEDA). The eyepiece system is optimized using imaging optical methods to project sub-beams to the target plane with a large angle. The sub-lens of condenser MLA is also optimized using imaging optical methods to refocus the collimating beam and match the numerical aperture (NA) with the eyepiece, and the sub-lens of the collimating MLA is acquired by using simulated annealing (SA) global illumination optics optimization method to achieve collimation and far-field homogenization. The predistortion MLEDA and the MLAs are proposed and implemented by the radial basis function (RBF) interpolation method, which correct the large-angle distortion introduced by the eyepiece. Both near-field and far-field applications can be realized by the proposed system. In the near-field applications, different spot geometries at the near-field target plane can be achieved. In the far-field applications, the power matching of the MLEDA is used to improve far-field uniformity of spot array. Moreover, the predefined-geometry arrangement spot array can be realized in both near and far fields. Two design examples with full field of view (FOV) projection of 80° and 100° are provided to validate the proposed method. Overall, the proposed system offers a promising solution for various applications requiring target identification or 3D calibration.

A 5.8 GHz 1.8 V +20 dBm 32.5% PAE Power Amplifier for a Short-Range Over-the-Air WPT Application.

This paper presents a 5.8 GHz differential cascode power amplifier for an over-the-air wireless power transfer application. Over-the-air wireless power transfer provides a variety of benefits in several applications such as the Internet of Things and medical implantation applications. The proposed PA features two fully differentially active stages with a custom-designed transformer to provide a single-ended output. The custom-made transformer shows a high quality factor, as high as 11.6 and 11.2 for the primary and secondary sides at 5.8 GHz. Fabricated using a standard 180 nm CMOS process, the amplifier achieves input and output matching of -14.7 dB and -29.7 dB, respectively. To achieve a high power level and efficiency, accurate optimization through power matching, Power Added Efficiency (PAE), and the design of the transformer are carried out while the supply voltage is limited to 1.8 V. Measurement results show a 20 dBm output power with a PAE as high as 32.5%, which makes the PA suitable for application, and it can be implanted while arrayed with various antenna arrays. Finally, a FOM is introduced to compare the performance of the work with similar works in the literature.

A Control Strategy for Achieving the Whole Operation Range Power Matching of Single-Phase Cascaded H-Bridge PV Inverter

The single-phase cascaded H-bridge (CHB) inverter can realize module-level MPPT. Its multi-level output voltage can reduce the volume of filter inductance and avoid using the power-frequency transformer. Therefore, the single-phase CHB inverter has a significant advantage in household photovoltaic (PV) power generation. However, due to the change of illumination conditions or damage of PV panels, the output power of H-bridges (HBs) will be unbalanced and result in the HBs with higher output power overmodulated, affecting the stable operation of the CHB system and the quality of grid current. In this paper, a control strategy is proposed to extend the operation range of the single-phase CHB inverter. The modulation strategy and reference power of each HB are adjusted according to the HB modulation index to achieve the whole operation range power matching. Compared with the existing methods, the proposed strategy further expands the operation range of the single-phase CHB inverter and ensures the full utilization of power transmission capacity of the system on the premise of stable operation and grid current quality. The simulation and experiment verify the effectiveness of the proposed strategy.

Battery-Based Energy Storage and SolarSolar Technologies Integrated for Power Matching and Quality Improvement Using Artificial Intelligence

Power quality issues, such as abnormal voltage, current, or frequency, can cause equipment malfunctions and failures, resulting in financial losses. With the developing integration of RES into distribution networks through custom power devices like electronic power cassette adapters, there is a need to address the challenge of integrating the variable output of RES into traditional grids. Energy storage systems are a potential solution, but they are costly for RES applications. This study proposes a hybrid solar structure combined with battery energy storage systems (BESS) to optimize power consumption and improve power quality using a meta-heuristic approach. The research methodology involves simulation using real solar PV data. The significance of the proposed approach lies in its potential to enhance power quality while utilizing the maximum capacity of BESS, thereby improving the integration of RES into distribution networks and mitigating financial losses caused by power quality issues.

Thermodynamic and economic analysis of an off–grid photovoltaic hydrogen production system hybrid with organic Rankine cycle

Water electrolysis technology is a potential approach for green hydrogen production and photovoltaic power consumption. However, due to the volatility and uncertainty of the solar energy, supplying photovoltaic power directly to the water electrolysis auxiliary system is instable. An innovative off–grid photovoltaic proton exchange membrane electrolytic cells hydrogen production system is proposed to address that issue. The system integrates an organic Rankine cycle system with evacuated tube collector modules to supply power for the auxiliary system. The electrical power generated by the photovoltaic module is directly supplied to the proton exchange membrane electrolytic cells. The matching of the organic Rankine cycle system output power and auxiliary system power demand has been conducted by comparing the temperature control methods and parameters. The thermodynamic and economic performances of the photovoltaic hydrogen production system have been investigated with the meteorological data of Nanjing. The results demonstrate the organic Rankine cycle system can completely satisfy the power demand of the auxiliary system operation. The annual hydrogen production of the system can reach 26.07 tons (316203.0 Nm3) and the hydrogen average electricity consumption is 4.75 kWh/Nm3. The system has a maximum energy and exergy efficiency of 8.8 % and 9.1 %, respectively. This system is suitable for retrofitting photovoltaic plants, the payback period of the retrofit project is 12 years, which shows higher profitability than that of grid-supplied hydrogen production.

Power Compensation Strategy and Experiment of Large Seedling Tree Planter Based on Energy Storage Flywheel

The intermittent hole-digging tree-planting machine shows a periodic short-time peak load law in planting operation, and the operation process is “idling” for small loads most of the time, leading to large torque fluctuations in the transmission system, unscientific power matching, and high energy consumption. To solve the above problems, this article proposes to use a series of energy-saving flywheels in the transmission system of the tree planting machine. On the premise of obtaining holes that meet the target young tree planting requirements, the optimal power compensation strategy for the flywheel system of the tree planting machine is studied to reduce torque fluctuations in the power transmission system, use smaller power drive units, and save energy. Firstly, the nonlinear multi-body dynamics simulation model of soil cutting by the hole-digging component is established. The boundary and contact conditions are set to simulate the power consumption of the hole-digging component at three rotating speeds. Based on the simulation results, the flywheel power compensation strategy is discussed, and the torque fluctuation of the flywheel balance system is analyzed. The results showed that the higher the speed, the greater the power consumption. The power value suddenly increased from 17.82 kW (1.28 s) to 27.93 kW (1.43 s) when the speed was 220 r/min. Then, the power value rapidly decreased, and the power consumption presented a short-term peak feature. The transmission system’s maximum input power is determined as 17.82 kW according to the various simulated power consumption characteristics. The part exceeding the power consumption is compensated by the energy storage flywheel. The total compensation energy was 2382.5 J. After the flywheel system was involved, the maximum output power of the tractor power output shaft decreased by 36.2%, and the peak torque decreased from 445.7 N·m to 285.1 N·m. The power consumption obtained from the field test and simulation was similar, but the energy required to overcome peak load was jointly provided by the flywheel and the engine. The actual input power of the power output shaft during the energy release period of the flywheel system was 18.51 kW when the rotating speed of the hole-digging component was 220 r/min, and the relative error with the simulation value was 2.43%. The measured actual speed reduction of the flywheel system was 8.9%. After installing an energy storage flywheel in the transmission system of the tree planting machine, the output power of the power unit can be stabilized. Tree planting machines can be equipped with smaller power units, which can reduce energy consumption and exhaust emissions.

Green power pricing and matching efficiency optimization for peer-to-peer trading platforms considering heterogeneity of supply and demand sides

Green power pricing and matching efficiency optimization for peer-to-peer trading platforms considering heterogeneity of supply and demand sides