Decrease Power Consumption Research Articles

MicroLEDs for optical neuromorphic computing—application potential and present challenges

Abstract The slow non-radiative surface recombination velocity of gallium nitride (GaN) in combination with its highly efficient radiative recombination makes this material ideally suited for microLEDs with dimensions as small as 1 µm and even below, serving as the fundamental building block of micro-displays. However, due to their superior miniaturization potential and energy efficiency, GaN-based microLEDs have applications that extend well beyond display technology. Their capability to produce optical patterns with high resolution, which can be modulated at extremely high frequencies, makes them suitable for numerous other applications. We suggest exploiting these exciting properties for a new and potentially equally significant application: utilizing microLEDs in optical processing units for artificial intelligence workloads. In neuromorphic computing, relevant aspects of biological neural networks are emulated directly with either electronic circuits or photonic devices, avoiding the shortcomings of conventional digital computer technology for AI workloads, which generally require massively parallel information processing. GaN microLEDs are discussed here as a promising enabling technology for optical neuromorphic processing units. We see great potential to substantially decrease power consumption through massively parallel in-memory processing combined with efficient photon production and detection. A theoretical analysis of scalability and energy efficiency is provided. A macroscopic bench-top optical microLED demonstrator is presented, which experimentally proves the feasibility of our approach. Future potential and challenges associated with miniaturizing and scaling microLED-based optical processing units are discussed. Finally, we summarize the open research questions that require attention before fully functional and miniaturized optical neuromorphic processing units based on GaN microLEDs can be realized.

A novel pulse liquid immersion cooling strategy for Lithium-ion battery pack

Ensuring the lithium-ion batteries’ safety and performance poses a major challenge for electric vehicles. To address this challenge, a liquid immersion battery thermal management system utilizing a novel multi-inlet collaborative pulse control strategy is developed. Moreover, different cooling methods (cooling structures, immersion coolants and pulse control method) are numerically investigated to assess their impact. Compared with other structural schemes, the battery module using baffles with fish-like perforations for the 5-in and 5-out scheme demonstrates superior cooling capability while reducing external power consumption. Furthermore, the utilization of FC-3283 exhibits better comprehensive performance compared to AC-100 and mineral oil. Notably, in terms of pulse cooling, when the output ratio reaches 50 %, the battery pack temperature can not only be maintained within a reasonable range, but also the time-averaged pump power consumption decreases by 87.6 % compared to the bottom inlet and top outlet scheme. At the same average flow rate, the liquid immersion battery thermal management system with output ratio of 25 % is the optimal choice for the trade-off between cooling performance and flow resistance, and compared with the bottom inlet and top outlet scheme, the maximum temperature and maximum temperature difference decrease by 23.7 % and 13.9 %, respectively.

Research on Energy-Saving Control Strategies for Single-Effect Absorption Refrigeration Systems

The automatic control device is a critical component of absorption refrigeration systems. Its functional enhancement can reduce operating costs, improve energy efficiency, and ensure long-term stable unit operation. Given that absorption refrigeration systems operate under various dynamic conditions, the rational design of control strategies is particularly important. This study analyzes the influence of changes in the cooling water and heat source water flow rates on the outlet temperature of chilled water in the unit based on the open-loop response characteristics of absorption refrigeration systems. It proposes a dual-loop energy-saving control strategy for single-effect hot water lithium bromide absorption refrigeration systems based on the setpoint comprehensive optimization algorithm. Considering the multiple variables, strong coupling, large inertia, long time delay, and nonlinear characteristics of absorption refrigeration systems, as well as the difficulties in modeling these systems, this study applies a model-free adaptive control algorithm to the system’s control. It derives both SISO and MIMO model-free control algorithms with time-delay components. Through simulations comparing MFAC, improved MFAC, and traditional PID control, the dual-loop energy-saving control strategy is demonstrated to effectively reduce system heat consumption by approximately 20%, decrease power consumption by about 10%, and enhance the system’s SCOP by approximately 19.3%.

Effect of Discharge Cooling using Condensate Water on the Performance of an Air Conditioner: A Field Testing

The effect of discharge cooling using condensate water from the evaporator on the performance of an air conditioner has been experimentally investigated. Instead of laboratory testing, the air conditioner was tested under real conditions, as is generally an AC unit installed in a room. The indoor unit was installed inside the room at a height of 2.6 m from the floor, while the outdoor unit was installed outside at floor level. In this research, the air conditioner was tested under two conditions, i.e., normal condition without discharge cooling and modified condition in which the condensate from the evaporator was flown and dripped to the discharge pipe. The use of discharge cooling could decrease suction and discharge pressure, as well as suction and discharge temperature. It also slightly decreases supply air temperature. Better performance of the air conditioner with the use of discharge cooling was shown by the decrease of power consumption by 3.5% and increase of cooling capacity by 2.45%. As a result, the coefficient of performance (COP) increases by 6.31%.

Impact of titanium modification on the performance improvement and phase change mechanism of ZnSb thin film

Phase change memory has emerged as a promising option for neuro-inspired and data-intensive AI applications, attracting significant attention from the semiconductor field recently. The performance of the device relies on the phase change material, aiming for enhanced thermal stability along with low power consumption. Nanocomposite ZnSb thin films with titanium dopant were prepared and their crystallization properties and mechanisms were investigated. Compared to pure ZnSb material, the addition of titanium can significantly enhance the temperature of crystallization and the 10-year data retention ability, both of which surpassing 16 °C. The obvious enhancement in thermal stability may be ascribed to the ionic bond formation between titanium and antimony elements, as indicated by differential charge calculations. Also, phase change memory cells with a diameter of 190 nm were fabricated using standard CMOS technology. The Ti-doped ZnSb thin film demonstrates rapid crystallization and amorphization within 50 ns while consuming low power at approximately 1.5 × 10−10 J. The decrease in power consumption may stem from the increase in band gap energy and a decrease in electrical conductivity, as confirmed by first-principles calculations. Both experimental and theoretical results prove that titanium doping can remarkably improve the physical properties of ZnSb thin film, facilitating the exploration and design of novel phase change materials with high thermal stability, low power consumption, as well as fast switching speed.

FSW of AA2024: effects of tool wear on energy consumption

ABSTRACT This study shows that the progressive adhesion of weld material to the tool in friction stir welding AA 2024-T3, up to tool saturation, brings about a decrease in power consumption until a plateau is reached. The cause of this behavior is the hindering of the stirring action of the tool due to the material accumulated on it. The built-up material changes the nature of the tool/material interaction and then the friction condition at their interface. The direct consequence is a decrease in the shearing strain and therefore in the heat generated by friction. Bits of this adhering material break off from the tool at intervals. Macro and micro detachments are identified. Micro-detachments happen continuously at small periodic intervals and produce vibrations. The amplitude of these vibrations increases in all their characteristic spectral components up to tool saturation. Macro-detachments generate oscillations in power consumption and leave galling on the weld bead.

Developing an integrated simulator and optimizer model for liquid desiccant dehumidification system “LDDSim”

This study introduces “Liquid Desiccant Dehumidification Simulator” (LDDSim), a novel software tool aimed at simplifying the construction of adiabatic liquid desiccant systems, with a particular focus on innovative series two-stage regenerator configurations. LDDSim enables parametric studies and optimizations, enhancing system design and selection. Moreover, LDDSim facilitates thorough system analyses through informative graphical outputs and employs multi-objective optimization tools to boost efficiency. This paper outlines the software’s main inputs, outputs, subroutines, inference engine, and complexity analysis and verification using a real case study utilizing multiple-effect regeneration (MER). Results highlight the advantages of employing a series two-stage regenerator, such as lower power consumption and more flexibility in space compared to single-stage setups. Furthermore, system optimization efforts led to a significant reduction in power consumption while maximizing dehumidifier efficiency and moisture removal rate, yielding promising results with a 36.2 % decrease in power consumption, alongside a dehumidifier efficiency of 94.02 % and a moisture removal rate of 9.84 g/s. LDDSim is a valuable tool for engineers and researchers in liquid desiccant dehumidification systems for design, simulation and optimization.

Development of a new environmentally friendly and efficient centrifugal variable diameter metering device.

The design of the maize metering device involves centrifugal variable diameter pneumatic and cleaning mechanisms, aiming to enhance the performance and power efficiency of pneumatic maize metering devices. Leveraging the impact of changes in centrifugal diameter and the guidance and positioning of airflow, we optimize the hole insert, seeding plate, seed limit board, and integrated front shell. This optimization facilitates the adjustment of both the quantity and posture of seed filling. As a result, seeds can form a uniform flow within the annular cavity, reducing the wind pressure necessary for regular operation and decreasing power consumption. A quadratic regression orthogonal rotation combination experiment is conducted using a self-made experiment bench, considering ground speed, wind pressure, and seeding rate as the experiment factors. Furthermore, a comparative experiment involving a novel centrifugal variable-diameter type metering device. The results indicate optimal seeding performance when the ground speed is 13.2 km/h, the wind pressure is 1.2 kPa, and the feeding rate is 25 seeds/s. Under these conditions, the quality of feed index reaches 95.20%, the multi-index is 3.87%, and the miss index is 0.93%. Findings reveal that the developed seed metering device achieved a quality of feed index exceeding 93.00% across varying speeds of 12~18 km/h, aligning with the production requirements. Moreover, the actual power consumption of Type B and C is about 85.00% and 98.00% lower than Type A, standing at only 32.90 W at 18 km/h. The COP of Type C is about 86 times and 12 times that of Type A and B, respectively, meeting the demands for efficient production of maize seed metering devices. In comparison to traditional design and structural parameter optimization methods for maize seed metering device, this study is helpful to the sustainable development of maize industry and reduce environmental pollution.

A numerical study on summer operation performance of PCM wallboard cooling tower coupling system in hot-summer and cold-winter regions of China

The use of phase change materials in building envelopes shows promise in reducing overall building energy consumption. Researchers are focusing on designing optimal wall structures based on varying climate characteristics to enhance building energy efficiency. This study presents a novel system that couples phase change material wallboard with cooling tower. In the summer months, the system efficiently utilizes cooling water to dissipate heat stored in the phase change material during the day, thereby maximizing the utilization of the phase change material. The research includes the design and optimization of a southward prefabricated phase change material wallboard and evaluates the long-term performance of the phase change material wallboard cooling tower coupling system through a validated numerical model. The optimization findings indicate that the system achieves maximum energy savings with a cooling water flow velocity of 0.0125 m/s. Moreover, double-level control shows a substantial improvement in system performance compared to single-level control. Long-term operation results demonstrate that the phase change material wallboard cooling tower coupling system effectively reduces indoor heat gain during summer, with a cumulative indoor heat gain of −16.29 kWh/m2, representing a 343.5 % reduction compared to the common wallboard. The system has the potential to significantly decrease power consumption in air-conditioning systems, particularly in regions with hot summers and cold winters.

Effective incentive based demand response with voltage support capability via reinforcement learning based multi-agent framework

With the ongoing advancements in power grids, it is crucial to maintain a balance between energy generation and usage to ensure the stability of power systems. Any disparity between the supply and demand of energy can lead to increased expenses for utility companies and consumers, which might potentially result in a widespread failure of the grid. To tackle this problem, this study offers the implementation of the Voltage Capability Incentive-Based Demand Response (VC-IBDR) system, which utilizes a multi-agent framework. The main goal is to reduce power usage by providing financial incentives, while also ensuring that voltage standards are satisfied at each node. In this method, the aggregator agent coordinates demand response operations by interacting with household agents that are equipped with home energy management systems. Every household utilizes a disjunctively constrained knapsack problem optimization method to effectively organize the consumption of home appliances, considering customer preferences and dissatisfaction. During demand response events, the aggregator agent works together with household agents to optimize appliance schedules, ensuring that voltage levels at each node remain within acceptable levels. The simulation is performed to assess the efficacy of VC-IBDR on a feeder that provides service to 25 residential households. The findings indicate substantial decreases in power usage, with an average decline in demand of 4.20% at the feeder level and a 10.41% decrease in peak power consumption throughout the day. Furthermore, the voltage values at each node stay consistently steady within the range of 0.96 to 1.0 per unit throughout the day.

LACT: Liveness-Aware Checkpointing to reduce checkpoint overheads in intermittent systems

Intermittent computing supports execution of the systems experiencing frequent power failures, such as battery-less devices powered by energy-harvesting. In such systems, checkpoint and recovery is a commonly adopted technique, where volatile system states are regularly saved to Non-Volatile Memory (NVM), to preserve computing progress between power cycles. Since checkpoint involves a large number of NVM accesses, which is expensive in terms of both latency and energy, reducing its overhead has been a significant research challenge. In this paper, we present LACT (Liveness-Aware CheckpoinTing), a compiler optimization technique to minimize checkpoint overhead in intermittent systems. At the time of checkpoint execution, there exist dead values in general, which will not be used or overwritten in the future. LACT examines such liveness information, especially in arrays, based on compile-time analysis and excludes the dead values from the checkpoint to reduce required checkpoint data, which is a previously unexplored optimization opportunity. Our evaluation shows that LACT can reduce 46.4% of required checkpoint data without any runtime support, leading to reduction of 31.5% in execution time and a 5.2% decrease in power consumption on average. Our experiments in real energy-harvesting environment demonstrates that such improvement translates to a 31.6% improvement in end-to-end execution time.

Industrial Park low-carbon energy system planning framework: Heat pump based energy conjugation between industry and buildings

The accelerating urbanization, rapid industrial development, and excessive consumption of fossil fuels pose survival challenges such as energy depletion and environmental degradation for humanity. In the context of industrial park development, constructing a low-carbon energy system, increasing the proportion of renewable energy, enhancing energy-level matching, and utilizing heat pumps for deep waste heat recovery are effective approaches to reduce fossil energy consumption and alleviate environmental pressures. Addressing issues such as diverse thermal flows in industrial sites, complex electricity-heat-cooling energy demands, and unclear industrial-building energy coupling mechanisms, this paper proposes a two-stage planning framework, comprising the following five steps: (1) constructing a waste heat utilization system centered around heat pumps, (2) establishing a mechanism for matching heat sources, equipment, and thermal sinks, (3) establishing an energy conversion model and energy quality quantification system, (4) optimizing waste heat utilization path allocation, and (5) conducting a system energy flow analysis. Case studies demonstrate that the proposed system achieves optimized matching of multiple heat sources and sinks in industrial and building scenarios through thermal integration, meeting diverse energy demands in the park, including electricity, cooling, and multi-grade heat. After coupling with traditional steam pipeline networks, the annual total cost and annual steam power consumption decrease by 33% and 39% respectively, with a waste heat contribution rate of up to 26% and a renewable energy penetration rate of up to 25%, and a waste heat recovery system payback period of 6 years. By establishing an energy quality quantification system and conducting multi-objective optimization considering losses and economic costs, this paper provides Pareto frontier solutions, offering references for engineering proposals. The proposed networked waste heat recovery system is characterized by low energy consumption and high economic efficiency, effectively integrating the energy characteristics of industrial parks and demonstrating engineering applicability.

79‐3: Novel Mini‐LED Pixel Circuit with PWM Driving Method for Decreasing Power Consumption

This article proposes a mini‐LED pixel circuit that employs the PWM driving method to decrease power consumption. To achieve uniform current, the circuit compensates for threshold voltage variations of TFTs and VDD I‐R drops. Simulation results show that power consumption is ameliorated over 10.53% more than the 6T1C circuit.

Machine learning-based lightweight block ciphers for resource-constrained internet of things networks: a review

The increasing number of internet of things (IoT) devices, wearable technologies, and embedded systems has experienced a significant increase in recent years. This surge has brought attention to the necessity for cryptographic algorithms that are lightweight and capable of providing security in resource-constrained environments. The primary objective of lightweight block ciphers is to provide encryption capabilities with minimal computational overhead and decreased power consumption. As a result, they are particularly well-suited for use on devices that have limited resources. At the same time, machine learning methodologies have evolved into powerful mechanisms for the purposes of prediction, categorization, and system optimization. This study introduces a challenges and issues involved in integrating machine learning techniques with the development of lightweight block ciphers.

A 3D ray traced biological neural network learning model

Training large neural networks on big datasets requires significant computational resources and time. Transfer learning reduces training time by pre-training a base model on one dataset and transferring the knowledge to a new model for another dataset. However, current choices of transfer learning algorithms are limited because the transferred models always have to adhere to the dimensions of the base model and can not easily modify the neural architecture to solve other datasets. On the other hand, biological neural networks (BNNs) are adept at rearranging themselves to tackle completely different problems using transfer learning. Taking advantage of BNNs, we design a dynamic neural network that is transferable to any other network architecture and can accommodate many datasets. Our approach uses raytracing to connect neurons in a three-dimensional space, allowing the network to grow into any shape or size. In the Alcala dataset, our transfer learning algorithm trains the fastest across changing environments and input sizes. In addition, we show that our algorithm also outperformance the state of the art in EEG dataset. In the future, this network may be considered for implementation on real biological neural networks to decrease power consumption.

A systematic review on elliptic curve cryptography algorithm for internet of things: Categorization, application areas, and security

Cyberattacks on the Internet of Things (IoT) may be avoided by implementing cybersecurity protocols on IoT devices, platform packages, and Internet tools. A significant problem is developing a simple security mechanism suitable for resource-constrained IoT devices. Elliptic curve cryptography (ECC) is extensively utilized and well-suited for use in low-resource environments like smartphone devices. ECC utilizes short crypto keys with the same security strength as conventional cryptosystems, decreasing power consumption and enhancing device efficiency. This study comprehensively evaluates ECC data privacy and security techniques in IoT-based devices. The research also looked into other cryptography protocols that ECC may use to increase security and performance. The inclusion procedures were papers published between 2018 and 2023, written in English, and published in a peer-reviewed scholarly outlet. This research eventually reviewed 61 suitable publications in total. Compared to other cryptographic methods, the study discovered that ECC has received greater attention or is frequently employed in IoT-based systems. However, additional issues and concerns must be addressed, including efficient IoT device security, maintaining privacy, and device security against vulnerability assaults such as man-in-the-middle attacks. For the efficient security of the IoT-based system, an improved ECC-based algorithm should be developed to enhance the security and privacy issues of the IoT system.

Investigations of a turbine pre-swirl system with high temperature drop efficiency through the design of a novel vane-shaped receiver hole

The pre-swirl system, a vital system responsible for supplying cooling gas to the turbine blades. However, the pre-swirl system involves rotor-stator matching and intricate power-heat conversion challenges, which has led to a bottleneck in the development of its temperature drop potential. This study investigates the traditional pre-swirl system structure to identify factors limiting its temperature drop performance. A novel design idea is proposed to enhance the temperature drop performance by reducing the power consumption in the pre-swirl system. Subsequently, the structure optimization and performance improvement for pre-swirl system are conducted through the design of four vane-shaped receiver hole models. To assess the effectiveness of these enhancements, the thermodynamic and aerodynamic characteristics of the pre-swirl system before and after optimizations are evaluated using numerical simulations. Finally, the system temperature drop characteristics equipped with optimal receiver holes are thoroughly evaluated by experimental test analysis. The findings reveal that the new type of pre-swirl system, featuring a leading-edge vane-shaped receiver hole design and the removal of the cover-plate cavity, surpasses traditional designs. It exhibits a remarkable 35.3 % improvement in the receiver hole discharge coefficient, a 39.7 % reduction in system entropy increase, and a 6.36 kW/(kg/s) decrease in specific power consumption. Significantly, experimental verification demonstrates a 10 % increase in the nozzle pressure ratio, the temperature drop of pre-swirl system increased by 53.6 % from 23.5K to 36.1K, and the temperature drop efficiency of pre-swirl system increased from 0.567 to 0.872. Therefore, this study offers valuable insights for the design of high-performance pre-swirl systems, contributing to the overall improvement of turbine efficiency.

Managing and Decreasing Power Consumption of Devices in a Smart City Environment

As smart cities continue to grow and the number of connected devices increases, power consumption becomes a critical concern. By offloading computationally intensive tasks from resource-constrained devices to more powerful edge servers, energy efficiency can be significantly improved. The research proposes a framework for managing power consumption in smart cities by offloading computational tasks to edge servers. This approach, considering factors like device capabilities, network conditions, and energy profiles, can improve energy efficiency. The framework's effectiveness is evaluated through real-world data simulations and performance metrics. Results show that offloading tasks to edge servers significantly reduces power consumption, conserving energy and prolonging battery life. The framework's adaptability ensures optimal resource allocation, maximizing energy efficiency without compromising performance. This research offers practical solutions for sustainable and energy-efficient operations in smarter cities.

Low power nanoscale S-FED based single ended sense amplifier applied in integrate and fire neuron circuit

Current advancements in neuromorphic computing systems are focused on decreasing power consumption and enriching computational functions. Correspondingly, state-of-the-art system-on-chip developers are encouraged to design nanoscale devices with minimum power dissipation and high-speed operation. This paper deals with designing a sense amplifier based on side-contacted field-effect diodes to reduce the power-delay product (PDP) and the noise susceptibility, as critical factors in neuron circuits. Our findings reveal that both static and dynamic power consumption of the S-FED-based sense amplifier, equal to 1.86 μW and 1.92 fW/GHz, are × 243.03 and × 332.83 lower than those of the conventional CMOS counterpart, respectively. While the sense-amplifier circuit based on CMOS technology undergoes an output voltage deviation of 170.97 mV, the proposed S-FED-based one enjoys a minor output deviation of 27.31 mV. Meanwhile, the superior HIGH-level and LOW-level noise margins of the S-FED-based sense amplifier to the CMOS counterparts (∆NMH = 70 mV and ∆NML = 120 mV), respectively, can ensure the system-level operation stability of the former one. Subsequent to the attainment of an area-efficient, low-power, and high-speed S-FED-based sense amplifier (PDP = 187.75 × 10–18 W s) as a fundamental building block, devising an innovative integrate-and-fire neuron circuit based on S-FED paves the way to realize a new generation of neuromorphic architectures. To shed light on this context, an S-FED-based integrate-and-fire neuron circuit is designed and analyzed utilizing a sense amplifier and feedback loop to enhance spiking voltage and subsequent noise immunity in addition to an about fourfold increase in firing frequency compared to CMOS-based ones.

Optimization Design of a Winch Suction Underwater Dredging Robot Using Orthogonal Experimental Design

In marine engineering and water conservancy projects, dredging often occurs due to silt accumulation, which can impede the long-term development of water ecosystems and water storage systems. To enhance dredging efficiency and the performance of dredging machines, a novel type of winch suction underwater dredging robot was designed. Computational fluid dynamics software was utilized to establish a fluid model of the robot’s winch suction dredging device and conduct model simulation experiments. The simulation test results were used to investigate the factors influencing dredging performance and their impact laws. Five key factors—namely, the reamer rotational speed, reamer arrangement angle, water flow rate, inlet pipe diameter, and outlet pipe diameter—were selected for consideration. By setting up various sets of factor levels, the significant influence of different factors on dredging efficiency was examined. Analysis of variance was employed to analyse the results of the orthogonal experimental design, leading to the identification of optimal factor levels and the establishment of an optimal scheme group. The results of the optimal scheme were verified, demonstrating a 13.049% increase in dredging efficiency and a 19.23% decrease in power consumption of the sludge pump compared to the initial experimental setup. The performance of the optimal program surpassed that of all the experimental designs and met the design requirements.