Variable Speed Research Articles

A gray-box model for unitary air conditioners developed with symbolic regression

In this paper, we present the development of a gray-box model for unitary air conditioning equipment that can be trained with as little as 5 data points with higher accuracy on test data. The model utilizes the same model inputs as is typical in building energy simulation, and is accurate. While black-box models require large data sets to deliver accurate results, white-box models require higher computational and engineering efforts along with detailed knowledge of the system, and are often difficult to obtain. The model presented here addresses a hybrid solution that is a steady-state, component-based, gray-box model that requires inputs from the source and sink fluids and rated performance of the specific piece of equipment, only. The basic physics of a vapor compression cycle are captured in individual component models for the heat exchangers, compressor, and expansion valve. These components are generalized to eliminate refrigerant-side inputs. A key addition is the development of correlations for the overall heat transfer coefficient times surface area (UA) obtained from Symbolic Regression (SR). The model successfully predicts the cooling capacity, coefficient of performance (COP), and sensible heat ratio (SHR) for three state-of-the-art variable speed, split-system, air conditioning systems with capacities of 12.3(3.5), 14(4), and 17.6(5) kW(tons), achieving a mean absolute percentage error (MAPE) of less than 3.4%. These results suggest that the gray-box model can be useful in predicting the performance of similar systems in the future, which could be valuable for energy management and optimization purposes.

Experimental assessment of communication delay's impact on connected automated vehicle speed volatility and energy consumption

Communication delays within connected and autonomous vehicles (CAVs) pose significant risks. It is imperative to address these issues to ensure the safe and effective operation of CAVs. However, the exploration of communication delays on CAV operations and their energy use remains sparse in the literature. To fill the research gap, this study leverages the facilities at America Center of Mobility (ACM) Smart City Test Center to implement and evaluate a CAV merging control algorithm through vehicle-in-the-loop testing. This study aims at achieving three main objectives: (1) develop and implement a CAV merging control strategy in the experimental test bed through vehicle-in-the-loop testing, (2) propose analytical models to quantify the impacts of communication delay on the variability of CAV speed and energy consumption based on field experiment data, and (3) create a predictive model for energy usage considering various CAV attributes and dynamics, e.g., speed, acceleration, yaw rate, and communication delays. To our knowledge, this is one of the first attempts at evaluating the impacts of communication delays on CAV merging operational control with field data, making critical advancement in the field. The results suggest that communication delay has a more substantial effect on energy consumption under high-speed volatility compared to low-speed volatility. Among all factors examined, acceleration is the dominant characteristic that influences energy usage. It also revealed that even minor improvements in communication delay can yield tangible improvements in energy efficiency. The results provide guidance on CAV field experiments and the influence of communication delays on CAV operation and energy consumption.

Impact of boundary layer parameterizations on simulated seasonal meteorology over North-East India

This study evaluated the accuracy of six planetary boundary layer (PBL) parameterization schemes in simulating two different seasons of pre-monsoon and monsoon in India's North-East region through the Weather Research and Forecasting (WRF) model. Twelve one-month simulations were conducted with the PBL schemes, six each for April (pre-monsoon) and July (monsoon), and the model outputs were compared against observations. Three non-local schemes, Asymmetric Convective Model (ACM2), Yonsei University (YSU), Shin-Hong (HONG), and three local schemes, Quasi Normal Scale Elimination (QNSE), Mellor Yamada Janjic (MYJ) and Mellor Yamada Nakanishi Nino (MYNN3), were tested. The meteorological variables of temperature, relative humidity (RH), wind speed, wind direction, and rainfall were evaluated, and the performance of each scheme for each meteorological variable is reported. The 2m temperature (T2) variable was well simulated by ACM2, MYJ in April, and YSU in July, while MYNN3 best simulated the 2m RH (RH2) during both seasons. 10m wind speed (WS10) and directions (WD10) were better simulated by MYNN3, HONG and YSU. HONG also best-simulated rainfall in April and MYJ in July. April and July being rainfall periods, an analysis of the schemes’ simulated rainfall frequency was also carried out. Moreover, the PBL schemes were also ranked, considering their combined performance with all the above meteorological parameters. While considering both the seasons and all meteorological variables, the scale-aware scheme, HONG, was the best scheme and can be used to simulate both seasons. Additionally, an in-depth analysis of surface and atmospheric parameters was also carried out to reason the simulated meteorology. QNSE expends the highest amount of its surface energy through surface evaporation, leading to the lowest surface skin temperature and T2 predictions. In contrast, MYNN3 produced the lowest mixing, which caused the moistest boundary layer, highest RH, cloud cover, and highly overestimated rainfall. Besides evaluation, which will help to choose a suitable PBL scheme for weather predictions in this region, this study also identifies the characteristics and deficiencies of PBL and surface layer schemes for improvement.

Multi-population coevolutionary algorithm for a green multi-objective flexible job shop scheduling problem with automated guided vehicles and variable processing speed constraints

Multi-population coevolutionary algorithm for a green multi-objective flexible job shop scheduling problem with automated guided vehicles and variable processing speed constraints

Evaluation method and enhanced strategy for frosting suppression performance of variable speed air source heat pump based on frosting suppression performance map

It is well established that the configuration and operation of variable speed air source heat pumps (VS ASHPs) can significantly influence their frosting performance. However, there is currently no effective method to conveniently and accurately evaluate the frosting suppression performance of these units. This paper addresses this gap by proposing a novel evaluation method based on a frosting suppression map for VS ASHPs. Firstly, an experimental setup with four ASHP units and developed frosting suppression maps is described. Second, a method for evaluating the frosting suppression performance of VS ASHP is developed based on the map. Thirdly, a comprehensive evaluation of the frosting suppression performance of the experimental unit is carried out. It is shown that the β values of the four units under the constitutive configuration were 0.74, 0.12, 0.21, and 0.52, and the frosting suppression performance was evaluated as Good, Poor, Fair, and Average, respectively. It could be enhanced and improved to 0.89 (Excellent), 0.24 (Fair), 0.64 (Good), and 0.63 (Good) after applying the frosting suppression operation method. The proposed novel frosting suppression evaluation method is simple and easy to implement, which could contribute to further guiding manufacturers to improve the frosting suppression performance of VS ASHPs.

Biokinetic modeling approach to investigate the impact of rotational speed variations in modified rotating biological contactors for palm oil mill effluent treatment

Palm oil mill effluent (POME) contains high organic content, posing significant environmental challenges that demand effective treatment solutions. Conventional rotating biological contactor (RBC) used for POME treatment are limited by insufficient surface area for microbial growth and inefficient oxygen transfer, limiting their effectiveness. This study enhances RBC systems by incorporating bioballs to increase microbial attachment surfaces and improve treatment performance. Experiments were conducted at various rotational speeds, and biokinetic modeling was applied under unsteady-state conditions. The results showed that the RBC operated at 3 rpm achieved the highest removal efficiencies, with 67.4 % for SCOD, 92.4 % for TSS, and 73 % for NH3. The biokinetic model revealed that rotational speed did not significantly impact oxygen transfer, mainly during the aeration phase. Lower speeds optimized substrate degradation and microbial growth, while higher speeds caused biofilm detachment. The innovative use of bioballs improves POME treatment efficiency at lower speeds, offering a cost-effective solution.

SSO optimized FOFPID regulator design for performance enhancement of doubly fed induction generator based wind turbine system.

A wind turbine system (WTS) is a highly coupled and nonlinear system where the output power depends upon highly uncertain wind speed. Therefore, the quality of produced power becomes a challenging problem for researchers. Direct Vector Control (DVC) is a powerful and widely utilized power control strategy to deal with winds that vary rapidly and randomly. As a result, this article employed the newly developed Social Spider Optimization (SSO) technique to optimize the design parameters of Fractional-Order Fuzzy Proportional-Integral with Derivative (FOFPID) regulator to maintain the output power of the studied DFIG-based WTS at the rated value under dynamic wind conditions. The suggested FOFPID controller integrates the capabilities of the Fuzzy intelligent regulator and the Fractional-Order controller, enhancing DFIG current control while allowing independent control of active and reactive power. The approach is incorporated within the DVC strategy of the DFIG's rotor-side converter (RSC), replacing the conventional Proportional-Integral (PI) regulator in the internal current loops. Extensive performance evaluations are conducted under various operating conditions, including active power reference changes, parameter uncertainties, and rapid wind speed variations. Comparative analyses with SSO-optimized PID and Fuzzy regulators show that the FOFPID regulator performs better in terms of maximum overshoot, extreme undershoot, settling time, Total Harmonic Distortion (THD), and Weighted Total Harmonic Distortion (WTHD). The suggested FOFPID regulator also displays stronger robustness against parameters mismatch and weather change than other regulator architectures.

Reflection phenomena of thermoelastic plane waves on a rigid surface within a size-dependent elastic media

The current investigation aims to comprehend the spread of time-harmonic thermoelastic plane waves in an isotropic and homogeneous nonlocal elastic material without bounds, within the framework of the Lord–Shulman model and Eringen’s nonlocal stress model. Our analysis reveals two sets of coupled longitudinal waves and one independent shear-type wave. The coupled longitudinal waves experience dispersion and damping over time due to the dissipative nature of the L-S model. In contrast, the vertically shear-type waves exhibit dispersion characteristics due to the presence of nonlocality in the medium. Furthermore, we observe that the shear-type wave encounters a critical frequency, while the coupled longitudinal waves may face critical frequency conditions under certain circumstances. We explore the reflection of thermoelastic waves at a rigid, thermally insulated, and isothermal boundary of a thermoelastic half-space, particularly in the case of an incident coupled longitudinal thermoelastic wave. We determine the amplitude ratios of the reflected waves to the incident wave through analytical methods. For a specific model, we generate various graphs to analyze the behavior of phase speeds, attenuation coefficients, and reflection coefficients. To assess the impact of the elastic nonlocal parameter on the variations of phase speeds, attenuation coefficients, and amplitude ratios of the reflected waves, we present graphical representations. Notably, our observations indicate that all waves are influenced by the nonlocality of the medium. Longitudinal waves exhibit sensitivity to thermal parameters, whereas the shear-type wave remains independent of thermal effects. Furthermore, the presence of elastic nonlocality results in a reduction in the classical shear-type wave speed.

Vibration characteristics of rolling bearing cage under speed variation conditions

Speed variation conditions will deteriorate the stress state of the rolling bearing internal components and aggravate the vibration of the cage, thereby affecting the service life and reliability of rolling bearings. In this paper, a nonlinear dynamic analysis model of the cylindrical roller bearing is established considering the rubbing effect and hydrodynamic contact between the cage and the guiding ring, as well as the sliding between the cage and other rolling elements. The vibration characteristics of the cage is discussed under the start-stop conditions and different fluctuations of rotation rate. The results show that the vibration of the cage mainly occurs at the middle and late stages of the acceleration process, and the impact mainly occurs at the middle stage of the deceleration process under the start-stop conditions. Moreover, the fluctuation of inner ring speed will enhance the unstable motion of the cage, among which the vibration and impact of the cage are most severe under the rectangular fluctuation of speed, followed by simple harmonic and triangular fluctuations. The findings can provide a theoretical guidance for improving the performance of rolling bearings and ensuring their safe and reliable operation.

Load Monitoring Methods for Controlling Training Effectiveness on Physical Conditioning and Planning Involvement: A Narrative Review

Monitoring the training load during training is important for quantifying the demand on psychological and physiological responses. This procedure is achieved through subjective and objective methods applied to the control of the level of training, to the attainment of conditioning and performance goals, and to the prevention of injuries. Training load refers to either external load, such as the variables of speed, distance, accelerations, and decelerations, or internal load, which is related to the psychological and physiological responses during an exercise session or training period (e.g., rating of perceived exertion—RPE; and heart rate—HR). To measure external load, traditional methods include pedometers, accelerometers, global positioning systems, and volume load. For internal load, methods include RPE, training monotony, strain, and impulse, HR, hormonal and biochemical markers, and training diaries and questionnaires. The current review reinforces the assumption that the methods should be combined to improve confidence with the information, mainly when assessing internal load stress during training. Moreover, training load provides an objective assessment of performance levels and involvement in different training phases, thus providing relevant information to analyse strategies for the effectiveness of conditioning progress, performance enhancement, and injury prevention.

Application of Resonance Method in Composite Fault Diagnosis of Bearings

Poisson white noise is a more accurate representation than ideal Gaussian white noise for simulating the noise background during early bearing failures. In the context of strong Poisson white noise interference, the failure mode of rolling bearings usually remains undetermined. This paper proposes a new method for diagnosing unknown bearing faults in bearings, diagnosis is proposed, which effectively identifies unknown faults across various components. The theoretical characteristics of Poisson white noise are initially analyzed and discussed. Then, to extract potential fault characteristic information, a false characteristic frequency of bearing is constructed in the response spectrum, and the response results at this false fault characteristic are obtained. Finally, coherent resonance (CR) is introduced, and false frequencies caused by false faults are eliminated by defining a quality factor. To verify the effectiveness of the method, the experimental and simulation results were compared with the decomposition results of the SVMD algorithm. The SNR of the experimental signals for outer and inner ring faults under variable speed conditions increased to 8.62[Formula: see text]dB and 11.74[Formula: see text]dB, respectively. Results indicate show that this method not only successfully identifies fault features, but also exhibits a strong noise reduction effect.

Model-Based Assessment of Energy Efficiency in Industrial Pump Systems: A Case Study Approach

Outdated, oversized variable speed pump drives (VSDPs) in industry lead to sub-optimal energy efficiency and considerable energy losses. This paper proposes methods to develop 2D efficiency maps for motors, converters, and pumps using polynomial surface fitting, which enables efficiency evaluation in a wide operating range. The method was applied to an oversized VSDP in an industrial chilled water supply system, comparing the original system with five alternative VSDP combinations with high-efficiency motors and pumps. The five VSDP variants demonstrated average energy savings of around 30%, with the synchronous reluctance motor (SRM) configurations outperforming the induction motor (IM) configurations by up to 7 percentage points, particularly at low loads. The high-efficiency SRM-based 252-IE5 variant delivered the best overall energy performance, highlighting the benefits of optimised system sizing and motor selection for energy savings. The proposed method can be used in both industrial and residential applications and offers great advantages in process systems that require variable flow and pressure of water or other fluids during operation, such as HVAC, water supply and wastewater treatment, district heating, etc. The development of a VSDP drive with efficient energy optimisation is an interdisciplinary problem of mechanical and electrical engineering, and without the interaction of engineers from both fields the result will not be optimal. We try to present our method so that it can be a reliable tool for mechanical, electrical, and other engineers or researchers to assist them in finding possible energy savings, performing energy audits, and selecting the most suitable components when modernising existing or developing new systems.

Energy saving analysis for pump-motor set in water purification plant using variable speed drive.

The induction motor is known to be the most reliable motor in the industry and is also the most energy-consuming load worldwide. It is noticeable in some production areas that the use of a high-capacity induction motor is not required at some operating times, and therefore it is important to control the speed of the induction motor to suit the operating requirements and obtain highly efficient performance. This paper presents a case study of a drinking water purification plant that uses a variable speed drive (VSD) as a speed controller for one of its induction motors to drive the pump. The VSD is connected to the motor in question to regulate its speed and maintain the external pressure of the station at an appropriate value that ensures water delivery to all branches of the network. 24-hour power consumption measurements of the respective engine with and without the use of a VSD are studied and analyzed to determine the potential for energy savings. Finally, a case study simulation is presented to compare the simulation results with the actual results.

Blade tip clearance measurement method based on blade tip timing without the once per revolution sensor

Abstract The rotor blade tip clearance (BTC) of an aeroengine is a critical parameter that significantly impacts its performance and safety. Accurately determining dynamic BTC has been a focal point of research in experimental testing. Among the effective measurement methods for dynamic BTC, the laser triangulation method based on blade tip timing (BTT) stands out. However, this method typically relies on an once-per-revolution (OPR) sensor for rotor speed and blade serial number information during measurement, leading to increased installation and maintenance costs as well as additional measurement uncertainties. In response to this challenge, this paper presents two signal processing method that eliminate the need for an OPR sensor. The first method, referred to as "none OPR method 1," closely follows the measurement principles of the traditional method but employs a skewed dual light probe (SDLP) signal to extract rotational speed information, thus obviating the need for an OPR sensor. The second method, "none OPR method 2," introduces a novel data processing approach that enables BTC determination without any source of rotor speed information. Both methods utilize dynamic and static BTC matching techniques to identify blade serial numbers and achieve BTC measurement without an OPR sensor on a simulated rotor experimental bench. Comparative analysis with traditional method BTC measurements reveals that, under stable rotor speeds, all methods achieve similar levels of accuracy and repeatability errors within 0.025mm. However, when dealing with variable speed conditions, the traditional method's accuracy is significantly affected. None OPR method 1 mitigates the impact of rotor speed changes to some extent, while none OPR method 2 remains unaffected by such changes. Importantly, both none OPR methods demonstrate the capability to measure blade-by-blade tip clearances akin to the traditional method.

A novel scheme of condition monitoring and fault recognition based on time-shift multi-scale weighted slope entropy for rolling bearings under variable speed conditions

A novel scheme of condition monitoring and fault recognition based on time-shift multi-scale weighted slope entropy for rolling bearings under variable speed conditions

Application of a regularised Coulomb sliding law to Jakobshavn Isbræ, western Greenland

Abstract. Reliable projections of future sea level rise from the polar ice sheets depend on the ability of ice sheet models to accurately reproduce flow dynamics in an evolving ice sheet system. Ice sheet models are sensitive to the choice of the basal sliding law, which remains a significant source of uncertainty. In this study we apply a range of sliding laws to a hindcast model of Jakobshavn Isbræ, western Greenland, from 2009 to 2018. We demonstrate that a linear viscous sliding law requires the assimilation of regular velocity observations into the model in order to reproduce the observed large seasonal and inter-annual variations in flow speed. This requirement introduces a major limitation for producing accurate future projections. A regularised Coulomb friction law, in which basal traction has an upper limit, is able to more accurately reproduce the range of speeds from 2012 to 2015, the period of peak flow and maximal retreat, without the requirement for assimilating regular observations. Additionally, we find evidence that the speed at which sliding transitions between power-law and Coulomb regimes may vary spatially and temporally. These results point towards the possible form of an ideal sliding parameterisation for accurately modelling fast-flowing glaciers and ice streams, although determining this is beyond the scope of this study.

Reconfiguration and compensation design method for single-DoF closed-chain leg mechanism

Compared with a wheeled robot propelled by a rotary drive, a legged robot equipped with multiple motors on a single leg possesses superior adaptability, while at the cost of high energy consumption and less velocity. Inspired by the California mite, the design method of reconfigurable closed-chain leg mechanism with single degree of freedom (DoF) is proposed for effective striding and smooth propelling. Furthermore, the lower-mobility closed-chain leg mechanism is more appropriate for obtaining high frequency and fast movement with the merits of simple control system and rotary drive. Firstly, a reconfigurable design is performed in the swing phase for a high-knee motion intermittently driven by a walking motor through dynamic coupling. Secondly, its fluctuations in vertical displacement and horizontal speed are compensated through the contact outline curve and variable speed input in the supporting phase. Finally, the simulated performance is analyzed and compared, and a prototype is fabricated for fluctuating and obstacle-crossing experiments.

Design and matching control strategy of electro-hydraulic load-sensitive hydraulic power unit for legged robots

A hydraulic power unit is the core energy source of hydraulic legged robots, ensuring the robot's maneuverability and carrying capacity in complex terrains. However, its pressure and flow output are usually set to a fixed level under all working conditions, which leads to mismatched pressure and flow requirements of hydraulic drive units. This mismatch reduces the stability and control accuracy of the hydraulic drive units and results in significant energy waste. To address these issues, this paper proposes an electro-hydraulic load-sensitive hydraulic power unit and a matching control strategy to better align outputs with requirements, thereby enhancing energy efficiency. Firstly, with the variable speed servo motor driving axial piston pump as the core, the closed system working principle of an electro-hydraulic load-sensitive hydraulic power unit is proposed, and the mathematical model of key components exhibiting strong nonlinearity and time-varying parameters is derived. After that, a matching control strategy based on flow feedforward and pressure difference compensation feedback is proposed. Finally, simulations and experiments are conducted to verify the feasibility of the unit and its matching control strategy. This paper provides a new solution for the design and control of hydraulic power units, laying the groundwork for achieving high-performance hydraulic systems.

A Novel Enhanced Fire Hawks Optimization Approach for Improving the Efficiency of Converter‐Based Controllers in Switched Reluctance Motors

ABSTRACTSwitched reluctance motors (SRMs) have gained popularity in various industrial applications due to their advantages, including structural simplicity, high reliability, low cost, and operational stability over a wide speed range without relying on rare‐earth permanent magnet materials. However, these motors exhibit drawbacks such as weak torque density, low efficiency, and significant torque ripple, particularly in high‐speed operation. An efficient converter‐based control approach is proposed to manage speed and torque variations in SRM motors, addressing these issues. A multilevel converter (MC) is introduced as a fundamental component. The novel multilevel converter (NMC) accommodates SRMs with varying numbers of phases and exhibits quick demagnetization and excitation behaviors, enabling independent operation of each phase even during conduction overlaps. Subsequently, an effective controller is developed for the SRM motor, combining proportional integral derivative (PID) control with enhanced fire hawks optimization (EFHO). The EFHO optimizes the PID gain values to enhance controller performance. The converter operation minimizes torque ripple and facilitates speed management. The EFHO technique is a fusion of fire hawks optimization (FHO) and the sine cosine algorithm (SCA). This amalgamation improves the updating process of FHO by incorporating SCA. The proposed methodology is implemented in MATLAB and evaluated through various metrics, including SRM motor current, voltage, speed, and torque, under electric vehicle (EV) load conditions. Performance comparisons are conducted with traditional optimization algorithms such as the whale optimization algorithm (WOA) and ant colony optimization (ACO). The results validate the effectiveness of the proposed methodology in achieving improved SRM motor control and performance.

Optimizing quality and cost in remanufacturing under uncertainty

AbstractIn the context of growing sustainability demands, businesses are increasingly adapting their production practices by integrating remanufacturing. However, companies often face challenges in profitably implementing remanufacturing due to complexities arising from uncertainties in processes, product quality, and market conditions. This highlights the need for effective decision support in remanufacturing processes. Addressing this challenge, our research introduces an algorithm designed to identify cost-efficient process plans that optimize order fulfillment while considering a company’s specific capabilities and inventory levels. By modeling the remanufacturing planning process as a Markov process, our algorithm comprehensively accounts for both process-related and quality-related uncertainties. This approach enables the evaluation of all Pareto optimal process plans in terms of cost efficiency and reliability. We validate our methodology through a real-world application in the automation industry, specifically focusing on the remanufacturing of variable speed drives. This case study demonstrates the practical relevance of our approach and a potential for significant cost reductions, enhanced process efficiency, and improved labor productivity. Overall, businesses gain critical insights into the financial prospects of their remanufacturing efforts, identifying opportunities for optimization and expansion into new product quality categories. This enhances their economic potential and aligns with consumer preferences for distinct product qualities.