Control Engineering Research Articles

Electric vehicle power system in intelligent manufacturing based on soft computing optimization

Soft computing technology has attracted extensive attention in computer engineering and automatic control domains because it can deal with uncertainties, fuzziness, and complex practical problems. This study adopts a Genetic Algorithm (GA) in soft computing technology to realize the cooperative optimization of electric vehicle's dynamic and economic performance. The advantage of soft computing technology lies in its adaptability to uncertainty, fuzziness, and complex practical problems, making GA an effective tool for solving complex optimization problems. Firstly, the electric vehicles' power system structure and energy management strategy are investigated and analyzed. Secondly, the improved non-dominated sorting genetic algorithm II (NSGA-II) is selected to optimize the parameters of electric vehicles because of its simple operation and high optimization accuracy. Thirdly, NSGA-II is used to construct the electric vehicles' power and energy configuration, with power and economic performance as the main optimization objectives. Meanwhile, a fuzzy logic controller is designed to adjust the parameters of GA online, so that the optimization process is closer to the actual operating conditions. Finally, the relevant variables are selected to achieve the optimization goal, the optimization objective function and constraint conditions are established, and the model is simulated and evaluated. The results show that the optimized electric vehicle's acceleration time is remarkably reduced, the dynamic performance is improved by more than 7 %, and the power loss is reduced by 5 %. In addition, compared with the current multi-objective optimization model, this model enables electric vehicles to travel longer distances under the same power. This study provides a new idea and method for the performance optimization of electric vehicles. Moreover, it offers a valuable reference for the innovation and development of electric vehicle technology in the intelligent manufacturing field. This study indicates that electric vehicles could be more efficient, energy-saving, and environmentally friendly to serve people's travel needs in the future.

A high-resolution acoustic goniometer for characterizing sound diffuser reflections

Noise control engineering and architectural acoustics practice have widely applied diffusing elements and devices to create surface scattering and diffuse reflections. An acoustical goniometer in the form of a circular microphone array has been used to characterize scattered responses for various types of diffusing elements/devices. This research is also intended for experimental validation of diffraction simulations of diffusing devices based on the physical theory of diffraction (PTD). To cope with experimental challenges, particularly for the research in the physical theory of diffraction, an acoustic goniometer must achieve a high enough angular resolution in addition to fulfilling far-field requirements. This paper discusses practical implementations and experimental results of portable goniometers with a radius of up to five meters and an angular resolution of 1.25 degrees. The practical implementation is intended to be easily deployable in empty, indoor spaces of sufficiently large dimensions for scattered reflection characterization. This paper discusses an effort of increasing experimental efficiency of characterization procedures for oblique incidences.

Transition Metal Dichalcogenides in Electrocatalytic Water Splitting

Two-dimensional transition metal dichalcogenides (TMDs), also known as MX2, have attracted considerable attention due to their structure analogous to graphene and unique properties. With superior electronic characteristics, tunable bandgaps, and an ultra-thin two-dimensional structure, they are positioned as significant contenders in advancing electrocatalytic technologies. This article provides a comprehensive review of the research progress of two-dimensional TMDs in the field of electrocatalytic water splitting. Based on their fundamental properties and the principles of electrocatalysis, strategies to enhance their electrocatalytic performance through layer control, doping, and interface engineering are discussed in detail. Specifically, this review delves into the basic structure, properties, reaction mechanisms, and measures to improve the catalytic performance of TMDs in electrocatalytic water splitting, including the creation of more active sites, doping, phase engineering, and the construction of heterojunctions. Research in these areas can provide a deeper understanding and guidance for the application of TMDs in the field of electrocatalytic water splitting, thereby promoting the development of related technologies and contributing to the solution of energy and environmental problems. TMDs hold great potential in electrocatalytic water splitting, and future research needs to further explore their catalytic mechanisms, develop new TMD materials, and optimize the performance of catalysts to achieve more efficient and sustainable energy conversion. Additionally, it is crucial to investigate the stability and durability of TMD catalysts during long-term reactions and to develop strategies to improve their longevity. Interdisciplinary cooperation will also bring new opportunities for TMD research, integrating the advantages of different fields to achieve the transition from basic research to practical application.

Correlation relationships of processes in the combustion engine in the RDE test

The article presents considerations on the processes taking place in the combustion engine in the in real driving operating conditions of a vehicle performing the RDE (Real Driving Emissions) test. The tests were carried out using a passenger car with a spark-ignition engine. The processes considered in the article were related to the engine operating states, exhaust emissions and fuel consumption, and the vehicle speed, which determines the engine operating conditions. The RDE test were carried out using PEMS (Portable Emissions Measurement System) equipment, and the following variables were recorded: vehicle speed, control, rotational speed, relative torque and relative engine power, emission pollutant intensity of: carbon monoxide, hydrocarbons, nitrogen oxides and carbon dioxide, the intensity of particle number and the fuel consumption intensity. The recorded signals were digitally processed, and the statistical properties of the variables and the mutual relation between the engine operating states were examined. The properties of the measured variables were investigated in the entire RDE test and in its constituent phases: the first, corresponding to vehicle movement in cities, the second – outside cities, and the third – on highways and expressways. The pollutant specific distance emission and the particle number specific distance as well as the specific distance fuel consumption were determined in relation to the average vehicle speed, and based on these results, the exhaust emissions and fuel consumption characteristics were created. Correlational studies of the considered variables were also performed. Pearson's linear correlation coefficients for the measured variables combinations were determined.

Practical considerations for assessing crew noise exposure in armored vehicles.

Measurement and analysis of the continuous and intermittent noise produced by armored vehicle (AV) platforms, including the output from communications systems as experienced by crew, are necessary for the purposes of exposure prediction, to support the selection of hearing protection and communication devices, and to facilitate assessments of compliance with occupational health and safety legislation. Practical estimation of the personal noise exposure of AV crews requires the assessment of the vehicle, communications and special-to-role activity noise sources, and an understanding of how these sources combine. Procedures are described that consider instrumentation requirements, AV configuration and build standard, operating conditions representative of actual use, the application of speed thresholding to measurements, and derivation of communications noise levels. Real-world examples are given where these procedures have been applied to an in-service tracked AV to estimate crew noise exposure. The procedures and methods presented are a compromise between precision, repeatability, reproducibility, and pragmatism. Measurements of AV noise are expected to be obtained during the commissioning stage of vehicle design, immediately prior to the vehicle being put into operational service and following any major modifications to the vehicle to inform the necessary engineering, administrative, and personal protective equipment control measures.

Porous acoustic metamaterial for simultaneous control of high and low frequency machinery noise: Case study of a water pump.

An acoustic metamaterial (AMM) consisting of a porous material (melamine foam) layer above a symmetrical labyrinthine metamaterial, incorporating a micro-hole and micro-slit cover plate, is proposed to simultaneously mitigate low and high frequency noise from industrial machineries. Theoretical model of sound absorption by this AMM is developed and validated numerically and experimentally. Sensitivity analysis indicates that increasing the length of the labyrinthine pathway and cover plate thickness and decreasing the slit width, slit length, and hole diameter shifts the peak sound absorption to lower frequencies. This material is successfully applied as a sound absorptive enclosure of a 0.5 hp water pump to reduce its sound pressure levels across widely separated frequencies of 1414-2245 Hz (high frequency) and 176-222 Hz (low frequency). This study offers guidelines to noise control engineers for controlling low and high frequency noise in industrial machineries.

A comprehensive control paradigm for prescribed performance attainment in complex nonlinear systems

This paper presents a comprehensive control framework tailored for achieving Prescribed Performance Control (PPC) in the context of complex nonlinear systems, addressing multifaceted challenges prevalent in control design. The focus is on a control scenario characterized by the simultaneous presence of nonlinearity, external disturbances, time delay, and unknown control direction—issues that pose considerable obstacles for existing solutions. To surmount these challenges, our proposed approach integrates well-established techniques, including neural networks, Nussbaum-type gains, and adaptive control strategies within a unified control design framework. The specific technical challenge addressed in this work involves the effective management of these intricate complexities in Single-Input Single-Output (SISO) systems. Our contributions extend the theoretical foundations, presenting an ideal PPC control design and introducing two adaptive neural network-based control methods capable of accommodating both known and unknown control directions. Utilizing Lyapunov–Krasovskii functionals, we showcase a unique integration that surpasses a mere combination of individual techniques. This work advances the theoretical underpinnings of control engineering tailored for real-world scenarios. The proposed controller’s efficacy is validated through rigorous simulations and compared with recent results and benchmark PPC controllers, establishing its superiority in addressing the intricacies of complex control scenarios.

Variable target water level control method in front of sluice in flood storage area based on storage balance model

Abstract To prevent the increase in flood disaster frequency, scale, and impact degree, a flood control engineering system with flood storage and detention areas, embankments, and reservoirs as the main body has been formed. Flood storage area is the key to the flood control engineering system, and its water level control performance is directly related to the success of flood control. According to the actual situation, the flood evolution simulation model in the flood storage area is constructed to obtain the evolution information of any unit of flood in the flood storage area. The dynamic control judgment coefficient of the water level is calculated, and the dynamic control program of the variable target water level in front of the sluice is formulated. Water level control can be realized by executing the established procedures. The above experimental data show that the proposed method can effectively control the water level in the flood storage area within the range of 26.03m ∼ 29.12m, and the minimum value of the corresponding risk rate is 3%, which fully proves that the proposed method has better dynamic control effect on the variable target water level in front of the sluice.

Kinetic model of multi-component polyatomic gas mixture considering internal energy excitation

In this paper, a kinetic Boltzmann model equation with internal degrees of freedom is established for thermodynamic non-equilibrium multi-component polyatomic gas mixture by using continuous energy levels to deal with rotational energy and vibrational energy. The normalization and conservativeness of the kinetic model are analyzed and proved. Then, numerical algorithm and wall boundary conditions for solving the model equation are given. Then, normal shock-wave structure flow problem and pressure/temperature gradient driven micro-channel flow problem for the two-component gas mixture are used to verify the reliability of the model. The simulation results are in good agreement with those obtained by other methods, which verifies the reliability of the model and algorithm in this paper. Finally, taking 25 N attitude control engine two-dimensional profile as the object, the study for two-dimensional profile nozzle internal and external mixed flow problem is carried out, and the influence of different inlet rarefaction levels on the molecular transports of mixed flow field and the molecular transport phenomena of mixed flow field with different number of components are discussed.

Impacts of MTBE in gasoline on the tailpipe ammonia emissions from China-6 certified passenger vehicles

Postcatalyst ammonia emissions from gasoline vehicles recently received attentions because of their contribution to the formation of urban secondary aerosols. To better understand whether fuel formulation would curb ammonia, the influence of methyl tertiary-butyl ether (MTBE) additive in gasoline on the tailpipe ammonia emissions from six China-6 compliant vehicles was investigated over the World Harmonized Light-duty Test Cycle (WLTC) at −7 ℃ and 23℃. Ammonia emissions were measured with MTBE-free and 10% MTBE-containing China-6 compliant gasoline fuels on the test vehicles. At – 7 ℃, the ammonia emissions with and without MTBE addition ranged from 0.15-17.07mg/km and 0.81−25.13mg/km, respectively. At 23 ℃, ammonia emissions were 0−7.4mg/km for MTBE-containing fuel and 0−8.76mg/km for MTBE-free fuel. More ammonia emissions were often observed as a result of maneuvering of enriched air-fuel mixtures to improve the combustion inability after cold-start and for de-NOx purpose, called as “λ sweep” (λ is excess air ratio). Due to the oxygen-containing nature of MTBE, its addition favors ammonia reduction. It is noted that “λ sweep”, an engine control strategy injecting extra fuel to deplete stored oxygen in the catalyst and suppress transient NOx formation during reacceleration after prolonged deceleration, may contribute to ammonia emissions due to the use of enriched air-fuel mixtures.

Polymerizable deep eutectic solvent-gels synthesized in situ under molecular engineering control exhibit excellent adhesion, freeze resistance, as well as stretching and humidity sensing capabilities

Hydrogels generally do not adhere well to different substrates and freeze at sub-zero temperatures, limiting their application. In this study, the strategy of replacing water in hydrogels with deep eutectic solvents (DES) was used to address these challenges. Specifically, choline chloride (ChCl) as hydrogen bond acceptor, acrylic acid (AA) and itaconic acid (IA) as hydrogen bond donors and polymerizable monomers constitute PDES. Afterwards, PDES-gel (PG) was obtained by adding a thermal initiator to polymerize AA and IA in PDES. PG has the following characteristics, because PG is almost water-free, it has remarkable low-temperature tolerance without any phase change at −60 °C∼20 °C. Thanks to the carboxyl groups and chloride ions contained in PG, it can form non-covalent interactions such as hydrogen bonding and ionic interactions with different substrates, so PG can adhere to various substrate surfaces. Furthermore, the breaking elongation of the novelty PG was up to ca. 960 %, tensile strength ca. 1 MPa, outstanding transparency with an average light transmittance of about 95 % in the visible-light range. Ultimately, the novel PG exhibited certain capabilities for moisture detection and deformation sensing. The new PDES-gel material developed using PDES is expected to provide new ideas for the advancement of wearable devices.

Investigation of solution behavior of Differential Equations by Sumudu methods of random complex Partial Differential Equations

In this study, solutions of random complex partial differential equations were found using the two-dimensional Sumudu transformation method(STM). The initial conditions of a deterministic equation or the non-homogeneous part of the equation are transformed into random variables to obtain a random complex partial differential equation. With the help of the properties of two-dimensional Sumudu and inverse Sumudu transformation, an approximate analytical solution of a complex partial differential equation with random constant coefficients was obtained by selecting a random variable with an initial condition of Normal and Gamma distribution. The probability characteristics of the resulting solutions, such as expected value and variance, were obtained and graphically shown with the help of the Maple package program.

Hybrid golden jackal and golden sine optimizer for tuning PID controllers

In the domain of control engineering, effectively tuning the parameters of proportional-integral-derivative (PID) controllers has persistently posed a challenge. This study proposes a hybrid algorithm (HGJGSO) that combines golden jackal optimization (GJO) and golden sine algorithm (Gold-SA) for tuning PID controllers. To accelerate the convergence of GJO, a nonlinear parameter adaptation strategy is incorporated. The improved GJO is combined with Gold-SA, capitalizing on the expedited convergence speed offered by the improved GJO, coupled with the global optimization and precise search capabilities of Gold-SA. HGJGSO maximizes the strengths of two algorithms, facilitating a comprehensive and balanced exploration and exploitation. The effectiveness of HGJGSO is assessed through tuning the PID controllers for three typical systems. The results indicate that HGJGSO surpasses the comparison tuning methods. To evaluate the applicability of HGJGSO, it is used to tune the cascade PID controllers for trajectory tracking in a quadrotor UAV. The results demonstrate the superiority of HGJGSO in addressing practical challenges.

Atomic Nb-doping of WS2 for high-performance synaptic transistors in neuromorphic computing

Owing to the controllable growth and large-area synthesis for high-density integration, interest in employing atomically thin two-dimensional (2D) transition-metal dichalcogenides (TMDCs) for synaptic transistors is increasing. In particular, substitutional doping of 2D materials allows flexible modulation of material physical properties, facilitating precise control in defect engineering for eventual synaptic plasticity. In this study, to increase the switch ratio of synaptic transistors, we selectively performed experiments on WS2 and introduced niobium (Nb) atoms to serve as the channel material. The Nb atoms were substitutionally doped at the W sites, forming a uniform distribution across the entire flakes. The synaptic transistor devices exhibited an improved switch ratio of 103, 100 times larger than that of devices prepared with undoped WS2. The Nb atoms in WS2 play crucial roles in trapping and detrapping electrons. The modulation of channel conductivity achieved through the gate effectively simulates synaptic potentiation, inhibition, and repetitive learning processes. The Nb-WS2 synaptic transistor achieves 92.30% recognition accuracy on the Modified National Institute of Standards and Technology (MNIST) handwritten digit dataset after 125 training iterations. This study’s contribution extends to a pragmatic and accessible atomic doping methodology, elucidating the strategies underlying doping techniques for channel materials in synaptic transistors.

Reliability inference of a multicomponent stress-strength model for exponentiated Pareto distribution based on progressive first failure censored samples

Multicomponent stress-strength (MC-SS) analysis is crucial for risk management and decision-making in various fields such as engineering, manufacturing, and quality control. It helps in identifying vulnerable components and areas where improvements can enhance overall system reliability. A primary contribution of this research is the implementation of the progressive first-Failure censored (PFIF-C) scheme. This scheme offers a novel and efficient approach to time and cost censoring, surpassing many existing censoring schemes found in the literature. The current study investigates the issue of MC-SS reliability inference under PFIF-C from the exponentiated Pareto distribution. The reliability of the MC-SS system is considered under the condition that both stress and strength follow an exponentiated Pareto distribution with a common second shape parameter. The parameter estimates and reliability estimate of the MC-SS system is produced using the maximum likelihood and Bayesian procedures. The asymptotic confidence intervals and highest posterior density credible intervals for the MC-SS system reliability are produced. Bayesian estimates are yielded using Markov Chain Monte Carlo under both informative and non-informative priors, considering symmetric and asymmetric loss functions. In order to assess the efficacy of the suggested methodology, simulation analyses are conducted. According to the simulation data Bayesian estimates of the MC-SS reliability, employing both symmetric and asymmetric loss functions, consistently outperform maximum likelihood estimates in terms of estimated risks. In general, Bayesian estimates based on asymmetric loss function perform better than the other competing loss function. The procedure is further shown with one real-world data example about failure times of a specific software model to show how the recommended approach may be applied to assess the strength and stress of a multicomponent model.

Influence of wet–dry cycles on the disintegration characteristics of Cretaceous siltstone, China

Cretaceous siltstone, which is widely distributed in the Yichang region, is a type of soft rock characterized by its low strength and its susceptibility to softening and disintegration when exposed to water. To gain a better understanding of the impact of wet–dry cycles on the disintegration characteristics and mechanisms of Cretaceous siltstone, a series of rock disintegration experiments were conducted. These experiments involved microscopic structure analysis and solution ion concentration tests on the specimens. The results of the experiments revealed that with an increase in the number of wet–dry cycles, the Cretaceous siltstone progressively fractured and disintegrated, with larger fragments transitioning into smaller ones. Microscopic structure analysis indicated that continuous wet–dry cycles altered the specimen's microscopic structure, resulting in the formation of new microcracks and pores. The results of solution ion concentration tests showed significant mineral dissolution losses during specimen immersion in the solution. Furthermore, a comparative analysis of various disintegration parameters highlighted that each metric emphasized specific aspects of Cretaceous siltstone disintegration characteristics. Therefore, adopting a multi-metric approach allows a comparison of the validation and assessment of the disintegration features of Cretaceous siltstone from many aspects. Finally, based on the experimental findings, a concise description and summary of the disintegration mechanisms of Cretaceous siltstone under wet–dry cycle conditions are provided; then, combined with its disintegration mechanisms, engineering prevention and control suggestions for timely drainage and a reduction in thermal contact are put forward from the perspectives of waterproofing and heat insulation, which can be used for reference.

Modeling the aspect ratio of commercial catalysts

AbstractMathematical modeling plays a diverse and crucial role in the chemical industry and academia. This manuscript describes how the physical and mechanical engineering disciplines help the commercialization of catalysts from evaluation to scale‐up and manufacturing. Forming and shaping the catalyst is the first basic step in the catalyst manufacturing industry. Part A shows some of the classic process methods that are employed for this purpose. Catalyst extrudates require proper engineering and process control of their aspect ratio. Catalyst extrudates with a high aspect ratio tend to yield a low reactor fill due to a loose packing. Catalyst extrudates with a low aspect ratio tend to yield high pressure drop. Part B introduces the tensile strength of the catalyst in order to predict the aspect ratio of catalyst extrudates in commercial plants. A force‐balance between the tensile strength of the catalyst and the impact forces due to collision experienced during manufacture leads to the dimensionless group . The group allows to introduce and quantify the severity of equipment and the severity of entire commercial plants.

Study on Influencing Factors and Control Points of Design Estimate of Landscaping Engineering

In recent years, China’s landscaping projects have developed vigorously, and the growth rate of urban garden green space areas has been maintained at about 5%. Overall, with the development of the national economy and the support of macro policies, people’s demand for close to nature and beautify the environment is gradually increasing, which has brought new growth momentum for the development of the landscaping industry. Simultaneously, from the perspective of future economic development and urban development, the landscaping industry still has a lot of room for development. However, with the rapid development of landscape engineering, the problem of cost control of landscape engineering is becoming more prominent, the phenomenon of budget overestimation is common, and there are many factors affecting the cost of landscape engineering, which brings difficulties and challenges to the analysis of its influencing factors and cost management. How to scientifically analyze the influencing factors and control the cost has become an important link in the landscaping project. To solve the above problems, this paper takes the design stage of landscaping engineering as the background, takes the design estimate of landscaping engineering as the research object, through literature research and data collection, fully excavates the main influencing factors of the design estimate stage of landscaping engineering, analyzes the key points of cost control, and provides reference ideas and directions for the later cost management and control.

Status of Construction Safety in Local Road Bridge Construction and its Consequences in Project Implementation: A Study in Gandaki Province, Nepal

After federalization of Nepal, bridge construction in local roads by provincial levels is in increasing trend. Being highly technical and of risky nature, construction safety needs to be ensured in bridge construction. However, in countries like Nepal, safety issues are considered, with follow up measures, only after the accidents occur at construction sites. In this context, this study aims to assess the present status and consequences of construction safety in local roads bridge project implementation and explore some improvements measures. A quantitative descriptive design was adopted for the study and 30 completed bridge samples from Gandaki province were selected using convenience sampling. Data were collected using questionnaire survey with 56 participants directly related to bridge construction and policy implementation. This study revealed that most of the bridge construction sites have poor workplace safety and worker’s welfare, inadequate provision and use of PPE, lack of trainings and awareness to workers as well as the absence of safety plans and method statements. Similarly, provisions for unsafe supports, shoring, formworks, concreting, and demolition were not noticed. While the absence of safety supervisor, job safety analysis, recording and reporting accident and diseases was observed, abundant cases were found where less importance was given to construction safety and use of PPE undermining the engineering and administrative hazard control methods in road bridge construction. Slip/trip/low falls, hand/leg/head injury, falling from height, eye problem, injury during erections, vehicle and electric current, cost and time overrun, substandard quality, reduced workers’ productivity, increased workers turnover, low construction safety reputation of contractor, loss/damage of land, irrigation canal, drinking water scheme, dust/noise have been found as consequences of poor safety practices. This clearly indicates that present bridge construction safety practices are inadequate and need substantial improvements for better project implementation. The major areas of improvements include safety as first priority, willingness, awareness and commitment of management, contractor and worker, selection of competent workers, formulation of specific safety rules, regulations, codes and their strict enforcement, good communication, safety training and inspection, motivation, adequate budget provision in contract for safety, provision of PPE, feeling safety as self-responsibility and use of technologies as well.

Distortion Engineering: A Strategy to Modulate Molecular Upconversion with Molecular Cluster-Aggregates.

The rational engineering of molecules is a powerful chemistry tool of pivotal importance in the fields of molecular magnetism and luminescence. Hence, systems that can be modulated via molecular engineering and composition control are expected to present extra versatility regarding the tunability of their properties. This is the case with molecular cluster aggregates (MCAs), high nuclearity molecular compounds. Herein, we demonstrate how the union of both strategies, namely, composition control and molecular engineering, can be employed to enhance molecular upconversion in MCAs. This was achieved by doping a {Gd8Er2Yb10} MCA with CeIII ions. By replacement of the optically silent GdIII ions with CeIII, the upconversion mechanism is modified due to CeIII-mediated cross-relaxation. In addition to this effect, we could also engineer the degree of metal site distortion due to the larger size of CeIII ions, relaxing the selection rules and impacting the upconversion quantum yield and luminescent thermometry. Opto-structural correlations demonstrate that the presented molecular engineering strategy can be used to enhance the performance of molecular upconverters.