Energy-saving Ability Research Articles

An optimal energy consumption calculation method of hybrid electric vehicles with frequency distribution characteristics of driving conditions

For a series of problems in the design and optimisation of series hybrid electric vehicles caused by the driving condition input, such as a variety of user conditions, which may hinder the energy-saving ability of such vehicles. Condition construction will inevitably lead to information loss, and traditional design methods require high computational power and encounter a time disaster during the real-world condition data explosion. This study proposes a condition representation method with driving condition frequency distribution characteristics (DCFDCs) and an optimal energy consumption calculation method, that is, instantaneous battery energy balance solution and global battery energy balance correction (IBGB–GBEB) with DCFDCs. The energy consumption calculation results show that the proposed optimal energy consumption method can guarantee the accuracy of the energy consumption calculation and reduce the calculation time cost. The difference in fuel consumption between the optimal energy consumption method and the dynamic planning (DP) algorithm is only 2.50%, but the difference in the calculation time between the two methods is 87.00%. Furthermore, the practical example of hybrid power system (HPS) design parameter optimisation shows that the energy consumption calculation results obtained by the TDCR–DP and DCFDCs–MIGA methods are consistent, and the relative error is only 1.81%. However, the calculation time of the TDCR–DP method is 472 h, whereas that of the DCFDC–MIGA method is only 2.17 h, which is a calculation time reduction of more than 99.54%. The results highlight the effectiveness and time advantage of the optimal energy consumption calculation method with DCFDCs. This study can provide theoretical guidance and technical support for solving system optimisation problems caused by the explosion of driving condition data.

Cost-effective pearlescent pigments with high near-infrared reflectance and outstanding energy-saving ability for mitigating urban heat island effect

Cooling down the surface temperature of buildings and saving energy consumption are tasks of top priority in mitigating the urban heat island (UHI) effect. The bright and colorful pearlescent pigmented cool coatings with high near-infrared (NIR) reflectance possess promise in enhancing the reflective effect of solar light and the visual aspect, which is still an undeveloped domain. Herein, these novel solar reflective coatings containing mediums and pearlescent pigments with high NIR reflectance of 85% embodied obvious energy-saving effects on building materials. EnergyPlus software was used to simulate the energy-saving effect of four applied climate zones, including New York, Nanchang, Lima, and Brasilia. Compared to commercial pigments (Fe2O3, γ-Ce2S3) with similar colors, the RK 402 and RK 301 pearlescent pigments demonstrate superior energy-saving capabilities in Nanchang climate zone, and can save 1.00 kW h m−2 and 1.60 kW h m−2 annually, respectively. In the warmer climate zone of Brasilia, the highest energy-saving efficiency is 2.06 kW h m−2 over one year by RK 301 pearlescent pigment. After irradiated by an NIR lamp, the surface temperature of the RK 301 coating can be reduced by 34.8 °C compared with that of the Fe2O3 commercial coating, and that of RK 402 coating is 5.2 °C compared with the γ-Ce2S3 commercial coating. Furthermore, the 7-day field test also has consistent effect of cooling down the surface temperature. This work demonstrated that pearlescent coatings with brilliant colors have great potential for application as cold materials in building areas to mitigate the UHI effect.

Research on Gravity Energy Saving Reconstruction Technology of Circulating Cooling Water in Mechanical Ventilation Cooling Tower of a Steel Plant

There is a height drop in the rain area of the circulating cooling water in mechanical ventilation circulating cooling towers, resulting in the ineffective use of gravitational potential energy. High-level water collection is an effective way to reduce the energy consumption of the cooling tower. Based on this, aiming to solve the gravity energy waste problem of circulating water in the cooling tower of a steel plant, this paper innovatively puts forward the high-level water tank to utilize the energy-saving transformation technology of turbine power generation and pump power saving. Additionally, this paper explores the energy-saving effects of the two methods under different height drops. The results show that the maximum utilizable rain area height of the cooling tower is 5 m, while the annual electric energy output of turbine technology can reach 4.704 million kW·h. The high water collection technology can reduce pump power consumption and save up to 7.35 million kW·h per year of electric energy, maintaining a more significant energy-saving ability compared with the turbine power generation technology. In terms of performance, the design of a high-level water tank is to help eliminate rain areas and improve the heat exchange efficiency of water and gas, so that the water temperature of the outgoing tower is 0.13 °C lower than that of the conventional cooling tower. Meanwhile, the ventilation resistance in the rain area is weakened, the resistance coefficient can be reduced by about 40–50%, and the noise can be reduced by about 10 dB (A) under the action of the water collection device. According to the economic evaluation, the total cost of turbine power generation technology is 0.563 million dollars and the total cost of high-level water collection technology is 0.446 million dollars. The cost can be realized within two years, but the high-level water collection technology avoids additional pump maintenance costs and has better economy. This study provides a theoretical basis for the transformation and optimization design of mechanical ventilation cooling towers, and has important reference value.

Throttling Loss Energy-Regeneration System Based on Pressure Difference Pump Control for Electric Forklifts

At present, the hydraulic systems of electric forklifts and traditional internal combustion forklifts are mostly valve-controlled speed-regulation systems, which have large throttling losses and potential energy waste. To further improve the energy-saving ability of electric forklifts, the forklift’s common working conditions are analyzed in this paper. A throttling loss energy-regeneration system based on pressure difference pump control is designed, and the system’s working principle is described. Aiming to deal with the problem that the pump−valve compound speed regulation with constant pressure difference could not realize high controllability and energy saving at the same time, a control strategy for variable pressure difference pump−valve compound speed regulation based on pressure balance control is proposed. The handle signal is positively related to the target speed of the oil cylinder. In the low-speed stage, the closed-loop control of the actual output torque of the motor/generator keeps the pressure difference across the proportional throttle valve unchanged, and the speed adjustment is realized by changing the opening of the proportional throttle valve. In the high-speed stage, the valve opening area is kept unchanged and the target pressure difference is changed to achieve the target speed. Finally, the feasibility of the control strategy is verified through an AMESim simulation, and the minimum pressure difference switching point is determined through experiments. The experiments show that the system’s energy-saving efficiency can reach 21.5% under a 1 t load. With the increase in the load, the system’s energy-saving efficiency can be further improved.

Influence factors on illuminance distribution uniformity and energy saving of the indoor illumination control method.

This study investigated the influence factors of illuminance distribution uniformity and the energy-saving ability of the indoor illumination control system, which consists of a white light-emitting diodes (WLED) matrix and a tabletop matrix. In the proposed illumination control method, comprehensive effects of time-invariant and time-variant sunlight of the outdoor environment, arrangement of the WLED matrix, iterative functions selected for illuminance distribution optimization, and compositions of WLED optical spectra are considered. The non-symmetrical spatial distribution of WLED-tabletop matrices, the optical spectrum selection of WLEDs, and the shifting sunlight intensity introduce obvious influence on (a) emission intensity and distribution uniformity of the WLED matrix and (b) receiving illuminance intensity and distribution uniformity of the tabletop matrix. Additionally, the selection of iterative functions, the WLED matrix dimension, the target error coefficient in the iteration, and the optical spectra of the WLEDs cause non-negligible influence on the energy saving percentage and iteration steps of the proposed algorithm, influencing the effectiveness and accuracy of the proposed method. Our investigation provides guidelines for the improvement of optimization speed and accuracy of indoor illumination control systems, and the method is hopefully to be widely applied in manufacturing industry and intelligent office buildings.

Progressive development in hybrid liquid desiccant-vapour compression cooling system: A review

Over the past few decades, the air-conditioning (AC) sector has seen significant growth in liquid desiccant air-conditioning (LDAC) system technologies. The LDAC system has been considered as a viable substitute to vapour compression system (VCS) as a result of its exceptional temperature and humidity control and energy-saving ability. This study provides an overview of the developments associated with the incorporation of liquid desiccant technologies into VCS units to date. Various configurations of dehumidifiers and hybrid technologies have been compiled and analysed according to economic and environmental considerations. The operating principle of dehumidification and the regeneration process of a LDAC system are initially discussed. Afterwards, the numerous advancements in materials for liquid desiccant and dehumidifiers, which play a crucial part in the dehumidification and regeneration processes, are discussed. Numerous studies have demonstrated that by incorporating liquid desiccant systems with the VCS units, a comfort level of cooling can be achieved by employing a dehumidification process while providing 40–80% energy savings. This review article is beneficial to researchers since it identifies research gaps and explores prospective future research techniques to further enhance the performance of hybrid liquid desiccant-vapour compression systems..

Energy-Saving Control Method of Building Central Air Conditioning Based on Genetic Algorithm

In order to solve the problem of huge energy consumption of building central air conditioning, the water system of building central air conditioning was taken as the research object and the genetic algorithm of energy-saving operation and control of building central air conditioning based on MATLAB was designed, so as to build the energy-saving control system model of central air conditioning. On the one hand, the feasibility of the optimized algorithm to solve the energy-saving problem of central air conditioning was proved through the optimization of genetic algorithm. On the other hand, the energy-saving effect was demonstrated through the operation parameters and the variation of air-conditioning energy consumption before and after the experiment. The feasibility and rationality of genetic algorithm to improve the energy-saving effect of central air conditioning was verified by the comparison of the experiment. The results showed that in the design load range of 30%–70%, the average energy-saving rate of central air-conditioning compressor was 16.8%. The maximum energy-saving efficiency was 37.4%, and the minimum energy-saving efficiency was 15.5%. The average energy-saving rate of water system was 26.8%. Therefore, the genetic algorithm had fast convergence speed and high solving accuracy, which was beneficial to improve the energy-saving ability of central air-conditioning water system.

Active-passive dual-control smart window with thermochromic synergistic fluidic glass for building energy efficiency

Windows are the least energy-saving part of the building envelope. To realize building energy-saving, smart windows have been developed. However, traditional fully passive thermochromic smart windows cannot adjust their transparency according to the complex outdoor climate “intelligently”, and only adjusts the solar radiation, ignoring the indoor temperature increase caused by heat entering the room in the form of convection. Here, we embed poly (N-isopropylacrylamide) (PNIPAm) microgel into a highly transparent polyacrylamide (PAM) matrix, the PNIPAm-PAM hydrogel exhibits an ultrahigh luminous transmittance of 90.6% and solar modulation of 65.5%. By introducing nanoparticles into thermochromic hydrogels and combining the advantages of fluid glass in heat convection control, we develop a new type of active and passive dual-control smart window (APDC smart window) for the first time. In the indoor demonstration, it is proved that the smart window injected with 1-cm PNIPAm liquid has the best energy-saving ability, and the greenhouse installed with a 1-cm PNIPAm liquid smart window reduces the indoor air temperature by 15 °C compared with normal glass. In the outdoor demonstration, the indoor air temperatures of the APDC smart windows are reduced by ∼14 °C, ∼16 °C, ∼8.5 °C, and ∼9.5 °C respectively in different orientations of east, west, south, and north than normal glass window, and it is reduced by ∼4–8 °C compare with the 1-cm PNIPAm liquid smart window. This opens a new avenue for energy-efficient buildings and greenhouses.

Improved multi-dimensional dynamic programming energy management strategy for a vehicle power-split hybrid powertrain

Dynamic programming is a widely used algorithm to solve the optimal control problem for hybrid electric vehicle in the whole driving scenario, but the problems of interpolation error and dimensional disaster have not been completely solved. This study proposes an adaptive adjustment method to solve the interpolation error problem, in which the solution without theoretical error can be obtained at the cost of a tiny driving cycle accuracy. Furthermore, a dynamic equivalent consumption factor calculation method is proposed to analyze the change of energy storage quality in the battery pack and the instantaneous equivalent consumption of the motors. The effectiveness of the improved algorithm is verified on a passenger car with hybrid powertrain using planetary gear mechanism. The results show that the established multi-dimensional dynamic programming algorithm has a relatively stable energy-saving ability. The maximum gap of fuel consumption rate is 3.2% in the four test driving cycles. Besides, there is only a maximum difference of 0.29‱ between the original driving cycles and the new cycles generated by the adaptive adjustment method. And obvious dynamic equivalent consumption factor changes of 15.7% in WLTC-class3, 10.3% in CLTC-P, 11.8% in FTP75 and 11.0% in NEDC are observed through the proposed calculation method.

Polymeric Structure Evolution Behavior Analysis of Aluminosilicate-Based Smelting Slag

The physical and chemical properties of the CaO–SiO2–Al2O3–MgO slag system depend on structure evolution caused by the synergistic mechanism among the components at high temperature, especially the structural complexity of the anion group. In this study, Si–O, Al–O, and Al–Si–O anion groups were found in the high-temperature slag systems at 1773 K. The [Si2O5]2− (Q3) structural unit of the silicate polymer changed to [Si2O6]4− (Q2), [Si2O7]6− (Q1), and [SiO4]4− (Q0) as the binary basicity (R2) and ω(MgO)/ω(Al2O3) increased, while there was a trend toward a simplified structure. That is, the stability of each structural unit weakened, and the relative content of non-bridging oxygen increased. As a result, the degree of polymerization of slag decreased, and the experimental results of the relative content of non-bridge oxygen can be fitted well with the calculations from the reference documents. At the same time, the number of Si–O–Al structural units gradually decreased. The 27Al-MAS-NMR spectroscopy results showed that the structure of aluminate changed from [AlO4]5− tetrahedral structure to [AlO5]7− pentahedral and [AlO6]9− octahedral structure, and the degree of polymerization of the slag decreased. Comprehensive analysis showed that basicity controlled within 1.2 with the ω(MgO)/ω(Al2O3) ratio; less than 0.55 allows for suitable fluidity and energy-saving ability, which is beneficial for the stable and smooth production of the blast furnace.

Adaptive control algorithm with a retraining technique to predict the optimal amount of chilled water in a data center cooling system

We developed control algorithms based on one of three artificial-intelligence-based retraining techniques (sliding window, vector adaptation, and vector augmentation) to provide the optimal indoor temperature and save on the energy expenditure for cooling in data centers. The artificial neural network prediction model predicts the computer room air handler supply air temperature of a central chilled water system and is added to the control algorithm. The proposed algorithm can determine the optimal chilled water flow rate required to cool the server to the set temperature by using the predicted computer room air handler supply air temperature. We developed a control algorithm embedded in an artificial neural network predictive model that includes three retraining techniques. Afterward, we compared the control performance and verified its adaptability by using computer simulation. When using the algorithm with sliding window control, the root mean-squared error between the set temperature and the control temperature was 0.08 °C, the maximum error was 0.81 °C, and the cooling load was 21,026.27 kWh. The accuracy, stability, and energy-saving ability of the sliding window control algorithm were higher those of the other two algorithms, and its superior adaptability and scalability under changing environmental conditions were demonstrated.

Wide-Spectrum Modulated Electrochromic Smart Windows Based on MnO2/PB Films

Inorganic materials have been extensively studied for visible electrochromism in the past few decades. However, the single inorganic electrochromic (EC) material commonly exhibits a single color change, leading to a narrow spectrum of modulation, which offsets or limits the maximally energy-saving ability. Here, we present a wide-spectrum modulated EC device designed by combining the complementary EC nanocomposite of manganese dioxide (MnO2) and Prussian blue (PB) for enhanced energy savings. Porous MnO2 nanostructures serve as host frameworks for the templated growth of PB, resulting in MnO2/PB nanocomposites. The complementary optical modulation ranges of MnO2 and PB enable a widen-spectrum modulation across the solar region with the development of the MnO2/PB nanocomposite. The colored MnO2/PB device exhibited an optical modulation of 32.1% in the wide solar spectrum range of 320-1100 nm and blocked 72.0% of the solar irradiance. Furthermore, fast switching responses (2.7 s for coloration and 2.1 s for bleaching) and a high coloration efficiency (83.1 cm2·C-1) of the MnO2/PB EC device are also achieved. The high EC performance of the MnO2/PB nanocomposite device provides a new strategy for the design of high-performance energy-saving EC smart windows.

An environmental and economic evaluation of solar photovoltaic thermal dryer

The photovoltaic thermal (PVT)-based solar dryer is advantageous in terms of energy-saving ability, efficiency, self-sufficient design, and ability to work without any additional electrical energy requirement. However, there is a requirement for a comprehensive analysis of the energy, exergy, and environ-economic parameters for developing an efficient and sustainable PVT solar dryer. In this study, a PVT-based indirect mode solar dryer with forced convection has been fabricated and investigated in the environmental conditions of North-East India (Silchar latitude of 24.83°). Experiments have been performed to compare the drying characteristics of tomatoes with quality analysis under the open sun and solar drying conditions. A new mathematical drying model is proposed to predict the drying characteristics of tomatoes under both modes of drying. The average PVT dryer efficiency is 34.98%, higher than some of the published works of indirect mode solar dryers conducted under similar experimental conditions. The calculated values of drying effectiveness, collector efficiency factor, coefficient of performance, and heat utilization factor are 1.12–1.58, 0.011–0.029, 0.71, and 0.29, respectively. Furthermore, CO2 emission, CO2 mitigation and carbon credit earned parameters are evaluated for 10, 20, and 30 years of system life. Graphical abstract

Ruddlesden–Popper-Structured (Pr0.9La0.1)2(Ni0.8Cu0.2)O4+δ: An Effective Oxygen Electrode Material for Proton-Conducting Solid Oxide Electrolysis Cells

Proton-conducting solid oxide electrolysis cells (H-SOECs) have attracted a lot of attention due to their high efficiency, energy-saving ability, and environmental friendliness. The ideal H-SOEC ox...

Design, modeling and control of a reconfigurable variable stiffness actuator

This work presents a reconfigurable variable stiffness actuator (RVSA) based on a rotational spring mechanism (torsional spring) and a group of specially designed symmetrical S-springs. The variable stiffness mechanism (VSM) enables continuous stiffness regulation from compliant to almost rigid. Besides, the stiffness can be adjusted by only rotating the spring to change its effective beam length with a simple drive chain, which contributes to easy control, fast response, and well energy efficiency. The internal friction is weakened by the combination bearing design. The spring rotation needed is almost perpendicular to the forces generated by the springs, which helps to reduce the torque required to maintain or adjust the stiffness (i.e., resistance torque). Mathematical models of stiffness were established for this novel RVSA, and its design parameters were analyzed. A prototype of the RVSA was constructed, and experiments based on a feedforward proportional derivative (PD) controller demonstrated the effectiveness of the design. A case study for the device’s energy-saving ability was presented. The test results showed that the RVSA had potential in energy efficiency in several cyclic tasks.

Liquid Thermo-Responsive Smart Window Derived from Hydrogel

Summary Buildings account for 40% of global energy consumption, while windows are the least energy-efficient part of buildings. Conventional smart windows only regulate solar transmission. For the first time, we developed high thermal energy storage thermo-responsive smart window (HTEST smart window) by trapping the hydrogel-derived liquid within glasses. The excellent thermo-responsive optical property (90% of luminous transmittance and 68.1% solar modulation) together with outstanding specific heat capacity of liquid gives the HTEST smart window excellent energy conservation performance. Simulations suggested that HTEST window can cut off 44.6% heating, ventilation, and air-conditioning (HVAC) energy consumption compared with the normal glass in Singapore. In outdoor demonstrations, the HTEST smart window showed promising energy-saving performance in summer daytime. Compared with conventional energy-saving glasses, which need expensive equipment, the thermo-responsive liquid-trapped structure offers a disruptive strategy of easy fabrication, good uniformity, and scalability, together with soundproof functionality that opens an avenue for energy-saving buildings and greenhouses.

Control of electric drive powertrain based on variable speed control in construction machinery

To improve the efficiency of construction machinery driven by pure electric power and to reduce energy consumption, a variable-pressure differential control strategy based on variable-speed control for a quantitative pump load-sensing system is proposed. The scheme of quantitative pump load sensing system based on variable speed control is introduced. The advantages, control objectives, and control strategies of the proposed control system are analyzed in different working conditions using simulations and experiments. The results show that the proposed variable-pressure differential control strategy can substantially reduce energy consumption. In the no-load mode, the power consumption of the proposed system was approximately 33.3% lower than that of the traditional system. During the idle mode, the proposed system consumed no energy, while the traditional system consumed about 0.6 kW. The energy saving of the main pump in the low-speed and low-flow-rate case was about 38%. In the lifting and pressure-holding case, the motor of the proposed system consumed 17.3% less power than that of the traditional system. In all test conditions, the proposed system demonstrated a good energy-saving ability. In addition, the proposed system has a high response rate and smooth operation across different working conditions, which demonstrates good control performance.

Novel fuzzy modeling and energy-saving predictive control of coordinated control system in 1000 MW ultra-supercritical unit

In order to satisfy the growing demands of control performance and energy conservation in power generation process, a novel T–S fuzzy modeling method combined with the quantum artificial bee colony (QABC) algorithm is proposed and applied to the coordinated control system (CCS) of ultra-supercritical unit in 1000MW power plant. The T–S fuzzy modeling consists of the identifications of premise part and consequence part. In the premise part identification, the cluster number and initial cluster centers are obtained at first by using entropy-based clustering method. Secondly, the initial cluster centers are modified through QABC algorithm to guarantee the integral of data and avoid possible marginalization. Then, the consequence part is identified through exponentially-weighted least squares. Furthermore, on account of the obtained fuzzy model, an energy-saving predictive control (ESPC) algorithm based on the generalized predictive control is introduced. In the rolling optimization process of ESPC, the values of manipulated variables taken as energy consumption indicator are introduced into objective function to decrease the consumption of energy and improve the performance of control process. Meanwhile, the addition of manipulated variables constraints can obtain further improvements of energy-saving efficiency and control performance. The simulation results demonstrate the high precision of identified model and ideal performance along with energy-saving ability of ESPC.

Urban resident energy-saving behavior: a case study under the A2SC framework

A full understanding of the characteristics of urban resident energy-saving (ES) behavior is an important prerequisite for the creation of targeted policies. This study constructs a conceptual model of urban resident ES behavior, consisting of four dimensions: attitude, ability, situation, and custom (the A2SC framework). Then, urban residents of Jiangsu Province, China, were studied to assess interactions among the different variables as well as direct effects of variables on ES behavior. The analysis was conducted using a partial least squares structural equation model. Based on the analysis, targeted suggestions for ES behavioral guidance have been proposed. Primary conclusions are as follows: First, ES attitudes, customs, and situation can all directly and positively affect ES behavior; the influence decreased in sequence, with influencing coefficients of 0.367, 0.225, and 0.087, respectively. Second, ES ability did not impose a direct effect on ES behavior; however, it can indirectly promote the formation of ES behavior by mediating attitude, situation, and custom. Third, when considering the interaction among variables, ES ability, situation, and attitude significantly promoted the formation of ES custom. ES situation contributed to the formation of ES ability, while ES ability and situation were important foundations of ES attitude.

Performance study of a quasi grid-connected photovoltaic powered DC air conditioner in a hot summer zone

The composition and principle of an air conditioner driven by a quasi grid-connected photovoltaic (PV) system are investigated by analyzing the working principle of quasi grid-connected energy-saving technology. Various aspects, including the PV properties of solar cells, the working principle of storage batteries, the working characteristics of direct current (DC) compressors, and the energy efficiency and economy of solar-powered air conditioners, are considered in the analysis. After an experimental platform is set up, experimental tests are conducted using a conventional air conditioner. Experimental results, as well as the results of the economic analysis based on the experimental platform, reveal that a solar-powered air conditioner can conserve grid electricity by more than 67% and 77% during summer daytime and summer nighttime, respectively. The comprehensive energy efficiency ratio of a solar-powered air conditioner is 4.6 times higher than that of a conventional air conditioner. The air conditioner must run for a maximum of 4h during daytime and 2h during nighttime to maximize its energy-saving ability.