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Bicomponent spunbond hydroentanglement technology can break the interface between the two components by physical extrusion and shearing, thereby realizing the green and efficient production of high-strength microfiber nonwoven materials. Herein, we report a soft and fluffy bicomponent spunbond hydroentanglement nonwoven material using high-shrinkage polyester/polyamide 6 (HSPET/PA6) as the bicomponent. HSPET/PA6 hollow segmented pie composite fibers with different volume ratios were prepared by spunbond technology, the HSPET and PA6 segments were alternately arranged, and the interface was flat. The composite fibers were split by heat treatment. The dry heat shrinkage rates of the composite fibers were 8.45% (50/50) and 10.57% (70/30), and the boiling water shrinkage rates were 10.02% (50/50) and 12.27% (70/30). HSPET/PA6 hollow segmented pie microfiber nonwovens were prepared by hydroentanglement technology. After heat treatment, the fibers of nonwovens were further split and the HSPET fibers curled, giving the nonwovens a fluffy characteristic. By comparing the properties of HSPET/PA6 after heat treatment, the shrinkage effect of the water bath was obviously better than that of dry heat, and the split degree of fibers reached 81.97% (50/50) and 84.65% (70/30). Compared with polyester/PA6 nonwovens, the softness of HSPET/PA6 nonwovens increased by 45.1% (50/50) and 49.3% (70/30) after boiling water shrinkage. At the same time, the mechanical properties of HSPET/PA6 nonwovens were also improved. The successful fabrication of HSPET/PA6 microfiber nonwovens provides a new method for enhancing the softness of bicomponent spunbond hydroentanglement nonwovens.

In the present work, we unveil a facile and effective method to directly grow Ni–Mo–Co oxy-hydroxide–based 3-dimensional hierarchical nanostructures on carbon microfibers (nano-on-micro) by using a facile hydrothermal synthesis route. Further, the electrochemical activity for directly grown fiber electrode as well as electrode formed by slurry coating of active material formed after hydrothermal reaction has been investigated. In this study, the metal ratios (nickel and cobalt) were selected to cover the wide spectrum of the concentration in order to obtain the optimum concentration for the best electrochemical performance. Electrochemical analysis of these ternary metal oxy-hydroxide–based active materials on the carbon microfiber shows significantly high electrochemical activity with a specific capacitance of 519 Fg−1 in hydrothermally activated sample and 890 Fg−1 in a slurry coated sample (at 1 Ag−1). This simple technique provides a novel method to fabricate high energy-storage devices with the advantage of being lighter and flexible and can be easily integrated for various flexible electronic applications potential applications including e-textiles, personal electronics, military apparel devices, and antimicrobial and biomedical textiles.

Nowadays, the feeding systems of computer numerical control machine tools are lubricated by periodic oil supply or fixed stroke, the lubrication is insufficient in the case of high load and high-speed movement, and the lubrication is excessive during finishing and low feed rate. This study discusses the optimum lubrication timing of the feeding system. When the feeding system is moving, the servomotor torque value and current, accuracy, and oil film thickness are measured by sensors. Moreover, the lubrication characteristic model is validated and built by using the sensor values, and the optimal lubrication state estimation is obtained by using the back-propagation neural model. Then analyzed and feedback to the machine tool controller, to intelligent the lubrication system. According to the test, when the feed rate is increased by 5 m/min, the friction coefficient increases with rate, increasing the output of the frictional value of the work table by 6.90%. When the load is increased by 175 kg, the friction coefficient decreases with load, reducing the frictional value output of table movement by 6.71%. In the relationship between oil film thickness and current, the accuracy difference between the prediction and actual test results is less than 10%; in the case of the same accuracy, the oil supply frequency is reduced by 80%, and environmentally friendly machine tool has been achieved.

High failure rate caused by distributed driving and the model uncertainty of the four-wheel independent control electric vehicle (FWI-EV) bring motion-state-identified challenges. For solving the identified problem and achieving accurate motion states of FWI-EV, this paper designs an innovative motion state observer based on dual strong tracking filter (DSTF), which consists of vehicle and driving identification layers. The strong tracking filter (STF) with time-varying fading factor is firstly introduced in driving identification layer to rapidly and accurately identify the driving torque mutation of driving system. The driving torque mutation is considered in the vehicle identification layer by data sharing between the two identification layers. The vehicle motion states fluctuated by driving torque mutation are accurately identified by vehicle identification layer based STF. The effectiveness of the design method has been validated by simulations.

Electrical discharge machining is an essential process in the domain of micromachining. However, many issues need to be solved to implement it in the industrial field. Increasing the machining rate still remains a challenging task in case of micro electrical discharge machining. It becomes impossible to machine a microfeature at a larger depth. Numerous investigators have investigated the positive effect of assistance such as magnetic field and ultrasonic vibration. This paper the discusses machining performance by simultaneously applying the ultrasonic vibration and magnetic field to the machining zone in micro-electrical discharge machining. The process performance is analyzed by measuring the performance characteristics such as material removal rate and taper of the microfeature. The results confirmed that the cumulative effect of each assistance ends in a better material removal rate and low taper of the microfeature.

The charging and discharging performance of lithium-ion battery at low temperature will decline greatly, which seriously affects the adaptability of electric vehicles at low temperature. This paper proposes to use the inductance characteristic of the motor stator and the switching control characteristic of the motor controller to form pulse current in the battery, and realize the self-heating of the power battery at low temperature. Using this method the heating of the battery can be achieved without any additional hardware or cost. The experimental result shows the average temperature rise rate of the power battery reaches 2.88°C/min. And the influence of different parameters on the heating effect is analyzed through the experiments, including IGBT switching frequency, d-axis voltage, motor-rotor position, and battery internal resistance.

Although the electric vehicles (EVs) have become the main development of the automotive industry, there is still very limited knowledge about the design method of EVs’ body structure. This paper substantially increases this limited knowledge by developing an EV’s aluminum alloy body frame structure design (EVFD) method based on battery arrangements. The main concept of the EVFD approach is the development of the parametric knowledge base to facilitate performance driven design of body structure in concept design stage, including the battery sub-libraries designed by vehicle power performances and the modular body frame structure sub-libraries and cross section of profile sub-libraries designed by structure performances. The layout of vehicle is firstly determined based on battery volume which calculated on the basis of power performance of EVs. And then, the body frame structures are designed by multi-load topology optimization and multi-objective parametric optimization based on the body structure performance, considering the battery layout and its mass distribution. The developed body structure knowledge base is screened through comparing their structural mechanical properties. The feasibility and accuracy of selected EV’s aluminum alloy body frame structure is verified by experiment. In this paper, the case study demonstrates that the proposed EVFD method based on battery arrangement can be effectively used to design aluminum alloy body frame structure of EVs, which provides a reference to other EV’s body structure design. Due to the performance driven design concept employed, the designed body structure for EV meets the requirements of lightweight, dynamic performance, and structural mechanical properties.

Due to the random nature of renewable energy in the micro-grid (MG) configuration, the energy generators in such systems are not able to offer an uninterrupted power and a mismatch between the demand and generation will be occurred. To alleviate this unbalance, technically, conventional storage devices are one of the practical solutions to this issue. However, the implementation of storage system is not effective from the economic preceptive and, as an alternative, the battery of electric vehicle can be also embedded in the structure of the MGs. In this work, an ultra-local model (ULM) controller based on a single-interval type-II fuzzy logic (SIT2-FL) controller is applied for frequency regulation of multi-MG(s) with electric vehicles. In this scheme, the ULM controller plays a critical role in the reducing the dependency of the controller to the MG model. An extended observer error is embedded in the structure ULM controller to remove the uncertainties included in the system. The SIT2-FL is established as supplementary controller to remove the error of observer and further ameliorate the multi-MG performance. Comparative simulation analysis and robustness examination are made to ascertain the usefulness of the suggested ULM controller-based SIT-FL.

The COVID-19 pandemic ushered in rapid telehealth/telemedicine adoption. In this study, we (1) examined rates and correlates of telehealth (video call) use among those aged 70+, and (2) tested the significance of access to information and communication technology (ICT) device ownership and knowledge of how to use the internet and devices as telehealth-enabling factors. The Behavioral Model of Health Services Use served as the conceptual framework, and data came from the COVID-19 supplemental survey of the National Health and Aging Trend Study. Results show that telehealth use increased to 21.1% from 4.6% pre-pandemic. In logistic regression models without technology-enabling factors, older age and lower income were negatively associated with telehealth use; however, when technology-enabling factors were included, they were significant while age and income were no longer significant. Insuring that older adults have ICT devices and internet access may reduce health disparities and improve telehealth care delivery.

Optimization of vacuum cleaner fan components is a low-cost and time-saving solution to satisfy the increasing requirement for compact energy-efficient cleaners. In this study, surrogate-based optimization technique is used and for the first time it is focused on maximization of Airwatt parameter, which describes the fan suction power, as an objective function (Case II). Besides, the shaft power is minimized (Case I) as another optimization target in order to reduce the power consumption of the vacuum cleaner. 11 geometrical variables of 3 fan components including impeller, diffuser and return channel are selected as the optimization design variables. 80 training points are distributed in the sample space using Advanced Latin Hypercube Sampling (ALHS) technique and the outputs of sample points are calculated by means of CFD simulations. Kriging and RSA surrogate models have been fitted to the outputs of the sample space. Through coupling of constructed Kriging models and Multi-Island Genetic Algorithm (MIGA), the optimal design for each of the optimization cases is presented and evaluated using numerical simulations. A 20.22% reduction in shaft power in Case I and an improvement of 27.73% in Airwatt in Case II have been achieved as the overall results of this study. Despite achieving goals in both optimization cases, a slight decrease in Airwatt in Case I (−6.20%) and a slight increase in shaft power in Case II (+4.82%) are observed relative to primary fan. Furthermore, the Analysis of Variance (ANOVA) determines the importance level of design variables and their 2-way interactions on the objective functions. It was concluded that geometrical parameters related to all of the fan components must be considered simultaneously to conduct a comprehensive optimization. The reasons of enhancement in optimal cases compared with the reference design have been further investigated by analysis of the fan internal flow field. Post-processing of the CFD results demonstrates that the applied geometrical modifications cause a more uniform flow through the flow passages of the optimal fan components.

Multi-point forming (MPF) is widely used for three-dimensional (3D) curved surfaces, and the multi-point die (MPD) is reconstructed with the desired curvature and the compensated curvature which is caused by springback. Springback is affected by mechanical anisotropy of material in MPF. To predict the springback of anisotropy sheet in MPF process, the finite element models were established based on the three different yield criteria namely; von Mises, Hill's 48 and Yld2004-18p. To compensate the springback of anisotropy sheet, an algorithm with consideration of anisotropy for doubly curved sheet was proposed based on the results of the finite element simulation and the elastic perfect plastic biaxial bending model. The direct curvature adjustment (DCA) method and the Non-Uniform Rational B-Splines (NURBS) method are used to generate the die surface after springback compensation. The final shape of the workpiece is obtained by the execution of iterative compensation. The forming experiments were carried out and the results show that the anisotropic model is closer to the experiment than the isotropic model. Finally, the influences of blank thickness, part shape and forming radius on compensation accuracy were discussed to verify the applicability of the algorithm.

This paper primarily investigated the effect of fiber breakage defects on tensile properties of the unidirectional composite (UD) using the numerical simulation method. Different kinds of fiber breakage defects were firstly proved to exist in the UD according to the sub-micro computed tomography images at the microscale level. A strict random uniform distribution hypothesis was then proposed to introduce fiber breakage defects into the composite. Numerous microstructural models within random fiber breakage defects were created with the Monte Carlo method to analyze the fiber breakage defect effect on the UD. The results show that the tensile modulus of the UD was reduced by 17% when the fiber breakage defect volume fraction was only 1%, which indicates the effect of this kind of defect was very significant. The fiber volume fraction, defect volume fraction and property all have influences on the decrease of the UD caused by the fiber breakage defect. Finally, we derived a mathematical model to calculate the tensile modulus of the UD based on the numerical results. The proposed mathematical model has an application on the prediction of the axial modulus of the UD or the fiber tow containing large numbers of fiber breakage defects in the composites with complicated structure.

Recent analyses of environmental services products and practices in healthcare have covered the concepts of hygienically clean, mechanisms of cleaning, and comparison of reusable and disposable textile microfiber products. In 11 referred papers, it was discovered that three had sufficient factual errors to influence the citations found in the broader literature. This study evaluating these problematic papers is an obligation of the scientific community for accuracy. In light of newer data on the efficacy of important textiles for microfiber cleaning, these previous studies were reexamined to see if methodological corrections are needed. Closer investigation of the authors’ data was used to ascertain the validity of their initial conclusions. These current reevaluations reverse conclusions in these journal articles. It appears factors such as multi-variant statistical comparisons, combining variables, and use of extremely high inoculum for cleaning led to the wrong conclusions in these three papers. The revised results show that for hospital surface cleaning with reusable textile microfiber products, no detectable levels were found for two of the most challenging organisms for hospital-acquired infections, methicillin-resistant Staphylococcus aureus and Clostridium difficile. Commercial laundry was substantially better than hospital laundry and reusable microfiber products improved with use.

The jester embodies an ancient social institution, which serves a paradoxical purpose: to mitigate the excesses of power, while serving and supporting the ruler through a license to jest. The metaphor of the jester, used constructively, offers a unique window on the contradictions of organizational studies and their paradoxical role in relation to corporate practices. We explore how jesting may inform academic work through using humour and laughter to deconstruct organizational taboos and convey truth to power. We suggest that academic jesting constitute a wise and undervalued way in which management learning can occur.

The Corun hybrid system (CHS) is a deeply coupled multiple-input–multiple-output (MIMO) hybrid system. The two inputs are the torques of the two motors. The two outputs are the carrier speed and transmission output torque. Using the traditional control method, the multi-objective control quality cannot be guaranteed because of the adopted static decoupling method and proportional–integral–derivative (PID) controllers. In this paper, the problems of the traditional control method are carefully analyzed, and a new control method is proposed. Instead of static decoupling, dynamic decoupling is adopted to improve the decoupling control effect. A predictive functional controller instead of a PID controller is adopted to deal with the pure delay caused by controller area network (CAN) communication. The tracking effect of the target value is further improved by predictive functional controllers. For the two decoupled subsystems, that is, the integral system and the second-order underdamped system, two predictive functional controllers are designed. The new control method was verified by simulations and tests. The results show that the new control method is superior to the traditional control method for CHS.

With the aim of economy improvement, emission reduction and prolonging the battery service life, an adaptive parameter optimal energy management strategy is proposed for range extended electric vehicle and a method of multi-objective optimization (MOO) is proposed. Firstly, two strategies based on different threshold parameter types, namely velocity-switch-based multi-operation-point control strategy (MCS v–b) and power-switch-based multi-operation-point control strategy (MCS p–b) are designed. Then, the oil-electric conversion loss rate, comprehensive exhaust emission, and battery capacity loss rate are selected as the optimization objectives. The barebones multi-objective particle swarm optimization is applied in MCS v–b and MCS p–b for solving the MOO problem. The simulation results show a clear conflict that three optimization objectives cannot be optimal under the same solution. And then, the individual with optimal comprehensive objective is taken as the final optimization solution to evaluate the performance of the proposed methodology. As expected, the proposed MCS p–b has a positive effect on prolonging the battery service life while ensuring high fuel economy and low emission. Experimental test results thoroughly validate the proposed approach and this result can be used to improve comprehensive performance levels.

Contrary to the triumphalist rhetoric that describes the automotive industry as a lever for both regional development in North America and industrial upgrading in Mexico, this article argues that the formation of the Mexico–U.S. automotive complex has instead been consolidated on the basis of longstanding processes of uneven regional development. To make this argument, the paper examines how global economic restructuring, trade policies, domestic economic development processes, transnational firm decision making and the maintenance of the geopolitical border have reproduced extreme wage differences between the United States and Mexico, resulting in the creation of a regional automotive sector that is both highly integrated and highly unequal. In this scenario, both nations are home to profoundly different industrial landscapes: the U.S. hosts the highest value-added links of the production chain, monopolizing processes of innovation and scientific and technological knowledge production, while in contrast, Mexico manufactures the most labour intense and lowest value-added links of the automotive production chain. From this perspective, the Mexican economy can be essentially understood as an export manufacturing platform which derives its ‘competitiveness’ from the aggressive industry maintenance of low wages.

Rubber pad forming is one of advance processing technologies. With both rubber pad and die, the sheet metal is stamped into the required shapes. The shapes of the die directly affect the final shapes of the channels on the sheet. With the developments of micro-channels, a new kind of two-step channels is concerned gradually in many fields. Since there are waved structures in these channels, many beneficial functions are caused. However, the manufacturing of this new kind channels by rubber pad forming are still not meticulously researched. This article is focused on the rubber pad forming process of different two-step channels. Different two-step channels are designed and made. Based on both FEM and physical experiments, the forming processes of these new channels are researched. The forming results are discussed and compared with each other, the best design strategy is also proposed through results.

The influence of the electromagnetic parameters on the torsional dynamics of the electric vehicle powertrain is studied by considering the electromechanical coupling effect. By adding the electromagnetic torque on the drive side, the powertrain is simplified as nonlinear drive-shaft model. The number, stability, and bifurcation conditions of the equilibrium points of the nonlinear drive-shaft model are deduced. Based on the averaged equations and the amplitude-frequency response equation, the stability and bifurcation conditions, such as fold bifurcation and Hopf bifurcation, of the resonance curve are discussed. The influence of electromagnetic parameters on the torsional dynamics is studied by simulation. It is shown that with the change of the parameters, the number as well as the stability of the equilibrium points may be changed which is affected by fold bifurcation. It is also shown that the resonance curve may lose its stability when fold bifurcation happens. By limiting the parameters in the region without fold bifurcation, the unstable dynamics of the resonance curve can be controlled.

Objective: This study aims to investigate the elements of wayfinding in indoor complex healthcare environments. Background: The study replicates Ghamari and Pati’s 2018 study to identify the environmental attributes that attract eye fixation during wayfinding by objectively tracking eye movements and fixation as healthy subjects navigate through a complex, unfamiliar indoor healthcare setting. The study addressed what do people look at while navigating in unfamiliar healthcare environments? What are the relative time periods of eye fixations on different visual environmental elements of the healthcare-designed environments? And what role do visual environmental attributes in healthcare facilities, such as configuration, color, art, directories, maps, furniture, and so on, play during the wayfinding process. Method: Twenty-four adults in different genders and various age groups participated in this study and navigated five routes with different degrees of difficulty. The sequence of the destinations in this study was randomized. The data were collected by tracking gaze fixations while human subjects navigated an indoor complex healthcare environment. Results: The findings show that identifying signs (29.1%), informative signs (20.8%), and architectural features (11.3%) constituted the most frequent elements attracting gaze, substantially more than the other classes of information. Four types of signage (identifying signs, informative signs, directional, and safety/regulatory signs) were accounted for 62.3% of the total gaze fixation time. Conclusions: The comparison of the ordered list based on frequencies and time of eye fixations on various elements developed in Ghamari and Pati’s study shows a vast degree of similarities.

The existing studies on profile error analysis and machining accuracy measurement do not consider the impact of the theoretical errors on the machine tool accuracy measurement. Therefore, this study proposes an estimation method of the surface profile error based on the normal section plane, using the theoretical flank milled surface for comparison. This effectively improves the accuracy of profile error estimation. The theoretical flank milled surface is the surface machined by flank milling under ideal conditions. Hence, compared to the traditional analysis method based on the designed three-dimensional model of S-shaped test pieces, the calculated profile error of this method does not include theoretical errors, thereby eliminating the impact of theoretical errors on machine tool accuracy measurement and evaluation. First, an improved method for continuous parameterized dual spline interpolation was proposed. It simplifies the solution of the singular problem of the coefficient matrix of the spline basis function and obtains a continuous ideal machining tool axis trajectory surface with complete geometric characteristics. Next, a method for constructing the theoretical flank milled surface machined with a cylindrical milling tool using equidistant mapping characteristics was proposed; then, the differential transformation relationship at the cutting contact point of the curved surface under the influence of tool path errors was established. Furthermore, the normal section plane method based on the differentiation of the cutting contact point was proposed. The problem of solving the distance from a point to a surface is converted to the problem of solving the distance from a point to a curve in the normal section plane. This improves the accuracy of profile error estimation. The effectiveness of the method was verified by comparing the analysis results of the profile errors of a typical cylindrical surface with the point to surface and the point to curve methods.

In the process of sufficiently considering fuel economy of plug-in hybrid electric vehicle (PHEV), the working time of engine will be reduced accordingly. The increased frequency that the three-way catalytic converter (TWCC) works in abnormal operating temperature will lead to the increasing of emissions. This paper proposes the equivalent consumption minimization strategy (ECMS) to ensure the catalyst temperature of PHEV can work in highly efficient areas, and the influence of catalyst temperature on fuel economy and emissions is considered. The simulation results show that the fixed equivalent factor of ECMS has great limitations for the underutilized battery power and the poor fuel economy. In order to further reduce fuel consumption and keep the emission unchanged, an equivalent factor map based on initial state of charge (SOC) and vehicle mileage is established by the genetic algorithm. Furthermore, an Adaptive changing equivalent factor is achieved by using the following strategy of SOC trajectory. Ultimately, adaptive equivalent consumption minimization strategy (A-ECMS) considering catalyst temperature is proposed. The simulation results show that compared with ordinary ECMS, HC, CO, and NOX are reduced by 14.6%, 20.3%, and 25.8%, respectively, which effectively reduces emissions. But the fuel consumption is increased by only 2.3%. To show that the proposed method can be used in actual driving conditions, it is tested on the World Light Vehicle Test Procedure (WLTC).

AISI D6 (hardness 65 HRC) is one of the hard-to-cut steel alloys and commonly used in mould and die making industries. In general, CBN and PCBN tools are used for machining hardened steel but its higher cost makes the use for limited applications. However, the usefulness of carbide tool with selective coatings is the best substitute having comparable tool life, and in terms of cost is approximately one-tenth of CBN tool. The present study highlights a detailed analysis on machinability investigation of hardened AISI D6 alloy die steel using newly developed SPPP-AlTiSiN coated carbide tools in finish dry turning operation. In addition, a comparative assessment has been performed based on the effectiveness of cutting tool performance of nanocomposite coating of AlTiN deposited by hyperlox PVD technique and a coating of AlTiSiN deposited by scalable pulsed power plasma (SPPP) technique. The required number of machining trials under varied cutting conditions (speed, depth of cut, feed) were based on L16 orthogonal array design which investigated the crater wear, flank wear, surface roughness, chip morphology, and cutting force in hard turning. Out of the two cutting tools, newly-developed nanocomposite (SPPP-AlTiSiN) coated carbide tool promises an improved surface finish, minimum cutting force, longer tool life due to lower value of crater & flank wears, and considerable improvement in tool life (i.e., by 47.83%). At higher cutting speeds, the crater wear length and flank wear increases whereas the surface roughness, crater wear width and cutting force decreases. Chip morphology confirmed the formation of serrated type saw tooth chips.

The growing integration of renewable sources with grid poses challenges in the field of voltage and frequency control. This study features combined automatic voltage regulator and load frequency control model of a three-area power system network with each area containing thermal and diesel power plants along with the introduction of solar thermal power plant, wind, and geothermal power plants. The Harris Hawks Optimization (HHO) based centralized Model Predictive Controller (MPC) has been discussed and implemented for the effective and simultaneous control of voltage and frequency in all three areas of the wind integrated power plant. To further deal with increased oscillations in frequency profile of the system caused due to renewable integration, the electric vehicle (EV) participation has been considered in each area to provide an auxiliary control against frequency deviations. Effectiveness of the proposed EV based MPC-HHO algorithm has been successfully verified after adding different nonlinearities, parameter uncertainties, disturbances, and time-delays in the wind integrated power system.

Energy management is a fundamental task and challenge of plug-in split hybrid electric vehicle (PSHEV) research field because of the complicated powertrain and variable driving conditions. Motivated by the foresight of intelligent vehicle and the breakthroughs of deep reinforcement learning framework, an energy management strategy of intelligent plug-in split hybrid electric vehicle (IPSHEV) based on optimized Dijkstra’s path planning algorithm (ODA) and reinforcement learning Deep-Q-Network (DQN) is proposed to cope with the challenge. Firstly, a gray model is used to predict the traffic congestion of each road and the length of each road calculated in the traditional Dijkstra’s algorithm (DA) is modified for path planning. Secondly, on the basis of the predicted velocity of each road, the planned velocity is constrained by the vehicle dynamics to ensure the driving security. Finally, the planning information is inputted to DQN to control the working mode of IPSHEV, so as to achieve energy saving of the vehicle. The simulation results show the optimized path planning algorithm and proposed energy management strategy is feasible and effective.

Rail corrugation is very serious in Cologne egg fastener track; effective control measures are still lacking. The cause of the corrugation wear on a curved metro track is analyzed based on the friction-induced vibration theory. A finite element model is established to study the frequency domain and time domain features of the friction-induced oscillation of this system. The influences of the fastener spacing and the fastener support length on the corrugation wear are investigated to develop countermeasures. The simulation results show that the friction-induced vibration of the wheel-track system is the wavelength-fixed mechanism of the corrugation wear of rail of the curved Cologne egg fastener track. There are two reasons why the low rail corrugation wear is more serious. The contact resultant force between the low rail and the wheel is obviously bigger than that between the wheel and the high rail, resulting in a higher wear rate of the low rail. The contact force fluctuation of the low rail caused by the friction-induced vibration is more severe, resulting in a higher corrugation wear evolution speed on the low rail. The friction-induced oscillation cannot be eliminated only by adjusting the fastener support length and spacing. However, the long-wavelength corrugation wear instead of the more harmful short-wavelength corrugation wear can be produced by adjusting the fastener support length and the fastener spacing to alleviate the influence of corrugation wear on the vehicle-track system.

As one of the technology-intensive industries, the electric vehicle (EV) industry has attracted the attention of the Chinese government. It has provided various incentives for the purchase of EVs, including tax incentives, policy loans at preferential interest rates and the establishment of charging facilities. EV production technology developed rapidly and sales of EVs increased significantly during the 2010s. The role of the government seems to have been of vital importance to the rapid development of the EV industry in China. To improve this further, it would be helpful for the government to efficiently coordinate various policy measures benefitting the EV industry and create a more suitable social environment for consumers to use EVs. The government should also carefully consider how to improve the applicability of EVs in different regional surroundings. In addition, efficient collaboration between the electronics industry and the automobile industry would be critical.

Limited capacity and short life cycle of a battery are the major impediments in development of practical Electric Vehicles (EVs). Eco-driving is an optimization technique through which a velocity trajectory that consumes minimum energy is advised to the driver. However, presence of traffic signals to control large traffic network degrades the performance of eco-driving; as applying brakes to stop and then maximum re-acceleration to restart a trip consumes lot of energy. Eco-driving problem with multiple traffic signals and static model of battery has been proposed as Two Point Boundary Value Problem (TPBVP). TPBVP fails to solve multi-phase problem as a single phase due to discontinuity of the co-states at the junction, that is, start of a new phase. This paper investigates an optimal solution with both EV and battery dynamics in the presence of multiple traffic signals as Multi Point Boundary Value Problem (MPBVP) using multiple shooting technique. Traffic signals come at some intermediate points of a trip. MPBVP ensures continuity at the junction to solve the multi-phase problem as a single phase through inter dependencies between each phases. Goal of this work is not only to solve constrained eco-driving problem with traffic signals but also include charging and discharging limits on battery that indirectly improves battery’s life cycle. Results indicate that EV has crossed all the traffic signals during their green duration without applying brakes with also satisfying all the other constraints and continuity condition. Moreover, it can be seen that energy consumption using MPBVP is also marginally lesser as compared to TPBVP.

In order to study the effect of loading rate on fracture behavior of dam concrete, wedge splitting tests of various loading rates (0.1, 0.01, and 0.001 mm/s) are carried out on two kinds of full-graded dam concrete notched cubes with side lengths of 300 and 450 mm, respectively. Digital image correlation and acoustic emission technique are used to measure the deformation and acoustic emission parameters of the dam concrete. Test results show that: the peak load and fracture energy of dam concrete specimens increases with the increase of loading rate. And the higher the loading rate is, the fracture of concrete shows more obvious brittleness. Influenced by the boundary effect, the CTOD increases with the increasing of loading rate, however, the length of crack decreases as loading rate increases. With the loading rate increases, the energy mutation area is more obvious, while the accumulated acoustic emission energy is affected by both the loading rate and the maximum aggregate size. The number of acoustic emission three-dimensional locating points and the shear signal decrease with the increase of loading rate, which is attributed to that the faster the loading rate is, the less sufficient the development of micro cracks in concrete is. The test results can supply experimental data to the fracture mechanics of dam concrete.

To address a recent challenge related to broken spikes in premium elastic fastening systems that have led to at least ten derailments and require manual walking inspections as well as build upon mechanistic-empirical (M-E) design principles for future fastening system component design, this paper quantifies the vertical, lateral, and longitudinal fastening system loads under revenue service traffic in a curve that has regularly experienced spike fastener fatigue failures. Previous data has indicated that the high rail of Track 3 experienced the most failures at this location. The data from this investigation sheds light into why failures are more predominant at this location than others and how the vertical, lateral, and longitudinal loads cannot be considered independently. Specifically, while the magnitude of the applied loading was the lowest on the high rail of Track 3, the threshold for failure was also the lowest given the operations at this location led to unloading of the high rail, thus indirectly highlighting the importance of friction within a fastening system. The data also show the high rail of Track 3 was subjected to the highest L/V load ratios and was an outlier in the typical lateral load reversals applied likely leading to spike stress reversals and thus a shorter fatigue life. Finally, based upon the data, it is recommended that to mitigate spike failures, as well as similar fastener challenges in other track types (e.g. rail seat deterioration, etc.) railroads should ensure trains operate close to the balance speed and use fastening system that transfer loads through friction. This study also provides novel data for M-E design of fastening systems.

Front-line staff routinely exposed to aerosol-generating procedures are at a particularly high risk of transmission of severe acute respiratory syndrome coronavirus 2. We aimed to assess the adequacy of respiratory protection provided by available N95/P2 masks to staff routinely exposed to aerosol-generating procedures. We performed a prospective audit of fit-testing results. A convenience sample of staff from the Department of Anaesthesia and Pain Medicine, who opted to undergo qualitative and/or quantitative fit-testing of N95/P2 masks was included. Fit-testing was performed following standard guidelines including a fit-check. We recorded the type and size of mask, pass or failure and duration of fit-testing. Staff completed a short questionnaire on previous N95/P2 mask training regarding confidence and knowledge gained through fit-testing. The first fit-pass rate using routinely available N95/P2 masks at this institution was only 47%. Fit-pass rates increased by testing different types and sizes of masks. Confidence ‘that the available mask will provide adequate fit’ was higher after fit-testing compared with before fit-testing; (median, interquartile range) five-point Likert-scale (4.0 (4.0–5.0) versus 3.0 (2.0–4.0); P

Monitoring nonmotorized traffic is becoming increasingly common practice at local and state departments of transportation. These travel activity data are necessary to monitor the system and track progress toward active transportation policy and program goals. A common problem is that permanent count site data are often missing, making those sites less useful. Being able to accurately estimate those missing data records functionally increases the amount of data available to use by themselves as metrics for monitoring traffic but also makes available more data for factoring short-term sites. Using nonmotorized traffic counts from several cities in Oregon, this research compared the ability of day-of-year (DOY) factors, a statistical model, and machine learning algorithms to accurately impute daily traffic records for annual traffic estimation. Based on exhaustive cross-validation experiments using data not missing at random scenarios, this research concluded that random forest and DOY factor approaches could be used to impute daily counts for nonmotorized traffic but each approach comes with tradeoffs. Though for many missing data scenarios random forest performed best, this method is complicated to estimate and apply. DOY factor-based methods are simpler to create and apply, and though more accurate in scenarios with significant amounts of missing data, they were less flexible given the need for data from neighboring count sites. Negative binomial regression was also found to work well in scenarios with moderate to low amounts of missing data. This work can inform nonmotorized traffic count programs needing vetted solutions for traffic data imputation.

In this article, I develop and redirect Julian Henriques’s model of sonic dominance through examination of accounts of acoustic violence and torture involving headphones. Specifically, I show how auditory experience has been weaponized as an intracorporeal phenomenon, with headphones effecting a sense of sounds invading the interior phenomenological space of the head. By analysing reported cases of sonic violence and torture involving headphones through a composite theoretical lens drawn from the fields of music, sound and body studies, I argue that in saturating the head’s perceived interior with sound, perpetrators of violence perform sonic dominance across two interrelated levels: the subjugation of interiorized auditory space via the notion of flooding, in which attention is directed towards the experience of the body as a vessel for sound; and the resulting manipulation of phenomenological head–mind linkages, with emphasis on the head as a ‘space’ for both sound and thought.

Limited driving range and availability of charging infrastructures are still among the main barriers of adoption of electric vehicles (EVs) in the market. Combination of those limiting factors causes ‘range anxiety’ in EV users. While different EV battery technologies and charging infrastructures are under development, one short-term solution to reduce EV users’ range anxiety is to provide the EV user with an accurate range estimation. In this study, an EV range estimation technique is proposed that recognises the current driving pattern and then classifies it into one of the predefined clusters (driving modes). The future energy consumption per kilometre is then tuned according to the average energy consumption of each cluster. Having an updated energy consumption rate, the EV range is calculated based on the battery state-of-charge. Different features are considered for driving pattern clustering where ‘average speed’ and ‘average power’ were identified as the best choices for this application. The effectiveness of the proposed EV range estimator is validated using real driving data that gives an average error of 9% in EV energy consumption estimation ahead.

During the working process of high-speed multiaxis machine tools, inertial forces can cause vibration and deformation of mechanical structure, which lead to the dynamic error of tool center point (TCP) relative to worktable and can adversely affect the machining performance. Considering the varying feed positions and accelerations during machining, a parameter-varying multi-rigid-body dynamic model of a 3-axis gantry machine tool is proposed. This model represents the position dependent structural dynamics and inertial forces, which can simulate the dynamic error of TCP relative to worktable within the entire workspace. The results show that the dynamic error in one direction is affected by the feed motions of multiple feed axes. The magnitudes of the dynamic error significantly vary with the position of Z-axis. And the dynamic errors in Y- and Z-direction show different varying trends. Then the theoretical model is used to discuss the dynamic error and position dependency. The expressions of TCP dynamic response and inertial forces reveal the reason why the dynamic errors in Y- and Z-direction show different varying trends.

Flexible links are often part of massive aerospace structures like helicopter or wind turbine blades, satellite bae, airplane wings, and space stations. In the present work, a mixed variational statement based on intrinsic variables is derived for multilinked smart slender structures. Equations involved in the derivation do not involve approximations of kinematical variables to describe the deformation of the reference line or the rotation of the deformed cross-section of the slender links resulting in a geometrically exact formulation. Finite element equations are derived from weak formulation, which can analyze large geometrically non-linear problems. The weakest possible variational statement provides greater flexibility in the choice of shape functions, therefore reducing the associated numerical complexities. The present work focuses on developing a single integrated computational platform which can study multibody, multilink, lightweight composite, structural system built with both embedded actuations, sensing, as well as passive links. Validation of static mechanical and electrical outputs from 3D FE simulation and literature proves the efficacy of the computational platform. Dynamic results will be communicated in future correspondence. The computational platform developed here can be applied for monitoring and active control applications of flexible smart multilink structures like swept wings, multi-bae space structures, and helicopter blades.

In order to realize the integration of handling, lateral stability, rollover prevention, and ride comfort of distributed in-wheel motor drive electric vehicles (EVs), this study presents an integrated control strategy for distributed EVs based on states estimation through particle filter (PF) and nonlinear model predictive control (NMPC). To estimate the vehicle states including longitudinal velocity, lateral velocity, and sideslip angle, the random walk model is established to avoid complex tire forces calculation. Then PF completes estimation by measuring longitudinal and lateral acceleration and yaw rate. Considering handling, lateral stability, anti-rollover performance, and ride comfort comprehensively, proposed controller takes full advantages of distributed electric vehicle platform with four-wheel steering (4WS), four-wheel-drive (4WD), and active suspension technology to improve the overall performance in the NMPC structure. State/actuator constraints are also taken into account in the scheme. Finally, the co-simulation through commercial software Carsim and Simulink verifies the effectiveness of the vehicle states estimator and designed control algorithm. Results show that estimation error is controlled within 1% and overall performance of distributed EV is improved.

Energy management strategies are critical for hybrid electric vehicles (HEVs) to improve fuel economy. To solve the dual-mode HEV energy management problem combined with switching schedule and power distribution, a hierarchical control strategy is proposed in this paper. The mode planning controller is twofold. First, the mode schedule is obtained according to the mode switch map and driving condition, then a switch hunting suppression algorithm is proposed to flatten the mode schedule through eliminating unnecessary switch. The proposed algorithm can reduce switch frequency while fuel consumption remains nearly unchanged. The power distribution controller receives the mode schedule and optimizes power distribution between the engine and battery based on the Radau pseudospectral knotting method (RPKM). Simulations are implemented to verify the effectiveness of the proposed hierarchical control strategy. For the mode planning controller, as the flattening threshold value increases, the fuel consumption remains nearly unchanged, however, the switch frequency decreases significantly. For the power distribution controller, the fuel consumption obtained by RPKM is 4.29% higher than that of DP, while the elapsed time is reduced by 92.53%.

The objective of this research is to develop a novel correction mechanism to reduce the fluctuation range of tools in numerical control (NC) machining. Error compensation is an effective method to improve the machining accuracy of a machine tool. If the difference between two adjacent compensation data is too large, the fluctuation range of the tool will increase, which will seriously affect the surface quality of the machined parts in mechanical machining. The methodology used in compensation data processing is a simplex method of linear programming. This method reduces the fluctuation range of the tool and optimizes the tool path. The important aspect of software error compensation is to modify the initial compensation data by using an iterative method, and then the corrected tool path data are converted into actual compensated NC codes by using a postprocessor, which is implemented on the compensation module to ensure a smooth running path of the tool. The generated, calibrated, and amended NC codes were immediately fed to the machine tool controller. This technique was verified by using repeated measurements. The results of the experiments demonstrate efficient compensation and significant improvement in the machining accuracy of the NC machine tool.

A critical lever in the fight against poverty is to improve attitudes toward those living in poverty. Attempting to understand the factors that impact these attitudes, we ask: Does believing that meritocracy exists (descriptive meritocracy) sustain negative attitudes? Using cross-sectional (N = 301) and experimental (N = 439) methods, we found that belief in the United States as a meritocracy is associated with blaming people living in poverty and predicts negative attitudes toward them. Replicating and extending these findings, we experimentally manipulated beliefs in meritocracy and blame. Weakening American Dream beliefs predicted improved attitudes toward those in poverty. Understanding the nuanced role of belief systems in attitudes toward those in poverty provides strategies for promoting more positive thoughts and feelings.

This work presents an ecodesigning and operating performance improvement methodology in series-parallel Plugin hybrid electric vehicle (PHEV) in passenger car category, through optimisation of powertrain, considering gradeability overreaching rolling terrain. Designing involves consideration for power of prime movers and the geometric specification governing gear ratio, which is the teeth number. PHEV performance is measured in terms of various output characteristics, such as, fuel economy, emissions, vehicle weight, battery charge, maximum velocity and maximum acceleration etc. and such output indicators comprising both ecodesign and vehicle operating performance attributes, eleven in all, are considered. For optimisation, the design space is generated using NREL, ADVISOR simulator in accordance with Taguchi’s method. Multi-criteria optimisation is used to converge the aforesaid output indicators into a single one using TOPSIS, MTOPSIS, Grey Relational Analysis and their surrogate assisted evolutionary algorithm (SAEA) based solutions to select the best from. Such design solutions are tested with UDDS driving cycle for performance analysis; reflecting superiority of SAEA based results. However, best values of output indicators are not from a single solution but are spread over these SAEAs. While, gradability is embedded in the model, its variation as supplemental factor, together with total ownership cost, are included, for extended modelling to ascertain the suitability amongst SAEAs. To extend the test for suitability beyond one driving cycle, also a combined one is formed by integrating two other, namely NEDC and 1015Prius with UDDS. The simulation experiment results from combined driving cycle also indicate preference in favour of MTOPSIS-SAEA model, complying upto 25% gradability for rolling terrain, substantially better than the reference model while also ensuring savings in fuel cost by about 60% over the entire ownership period besides reduction in greenhouse gas emissions ranging between 18% and 21%. This solution also helps in lightweighting the vehicle by over 6%.

Accurately predicting the spatial distribution and charging demand of future electric vehicles (EVs) is vital to directing investment in charging infrastructure and planning policy interventions. To date, this expansion has been heavily concentrated in wealthy cities and suburbs, among commuters, and among households able to charge their vehicles at home. The expansion of EV ownership will include both changes in where the vehicles are owned and how they are used and charged. This paper demonstrates methods to predict where the expansion of EV ownership is most likely to occur under current market characteristics and allows for testing of scenarios of future characteristics. These methods are demonstrated with an analysis of California, U.S., using a scenario of 4 million battery electric vehicles (BEVs) and 1 million plug-in hybrid electric vehicles (PHEVs), to match the state’s goal of 5 million zero-emission vehicles by 2030. These projections are combined with a model for charging behavior to generate scenarios of demand for charging away from home under various fleet characteristics and identify areas of the state with the greatest need for infrastructure investment.

Speed estimation for the out-of-control truck on a downhill grade is essential for passive safety features like truck escape ramps to promote traffic safety. This paper presents a method for estimating the speed of out-of-control trucks based on Newton’s Laws of Motion. First of all, we analyze gravity effort, aerodynamics, and rolling resistance through a free body diagram of an out-of-control truck on a downhill grade. Further, we select the speed as the dependent variable, with the following road and vehicle characteristics as independent variables: road surface type, grade, grade length, truck size, truck weight, and tire type. Finally, we estimate the speed and acceleration according to Newton’s Laws of Motion. The results show that the factors that significantly affect the out-of-control truck’s speed include tire type, road surface coefficient, grade, and grade length. TruckMaker simulation results demonstrate that the model is valid at a 99% confidence level.

Safe and comfortable driving experience includes the improvement of handling performance and stability control. This paper proposed a coordinated controller based on the function allocation for the handling performance and stability of distributed drive electric vehicles. The proposed controller has three layers. The upper control layer designs a dynamic stability envelope boundary suitable for various driving conditions through the phase plane method, and on this basis, the function allocation rules of torque vector control (TVC) strategy and electronic stability control (ESC) strategy were formulated. The medium control layer used the robust [Formula: see text] dynamic output feedback control method and the improved particle swarm optimization (PSO) parameter self-adjusting method to calculate the additional yaw moment required by the TVC strategy and the ESC strategy, respectively. The two types of additional yaw moment are implemented by the in-wheel motor and the hydraulic brake mechanism respectively. The lower control layer optimized the four-wheel torque and braking force based on the optimal tire load rate using the quadratic programming method. The proposed coordinated controller was performed in the CarSim/Simulink co-simulation platform and tested in a real vehicle platform. The results show that the proposed controller can improve the vehicle dynamic response according to the driver’s intention, thus bringing the better handling performance and stability.

Purpose: To explore the possible challenges and difficulties of using Personal Protective Equipment (PPE) in ophthalmic practice during the Coronavirus disease 2019 (COVID-19) pandemic. Methods: This is a multicenter, international survey among practicing ophthalmologists across different countries. The survey was conducted from September 9th to October 24th, 2020. It included a total of 23 questions that navigated through the currently adopted recommendations in different clinical situations. The survey also assessed the convenience of using various PPE in ophthalmic practice and addressed the clarity of the examination field while using various PPE during clinical or surgical procedures. Results: One hundred and seventy-two ophthalmologists completed the survey (101 from Egypt, 50 from the USA, and 21 from four other countries). The analysis of the responses showed that most ophthalmologists use face masks without significant problems during their examinations, while face shields followed by protective goggles were the most inconvenient PPE in the current ophthalmic practice. Moreover, most of the participants (133, 77.3%) noticed an increase in their examination time when using PPE. Furthermore, a considerable percentage of the respondents (70, 40.7%) stopped using one or more of the PPE due to inconvenience or discomfort. Conclusions: Due to the unique nature of the ophthalmic examination, certain PPE are not ophthalmologist-friendly. Innovative PPE should be tailored for prompt, more convenient, and clearer ophthalmological practice.

Compression plates are widely used in orthopaedic surgeries for internal fixation of fractured femurs. To fix the plate and thus to provide compression to a fracture, the self-tapping bone screws are tightened through predrilled pilot holes of smaller diameter. Preliminary investigation showed that the holes drilled with the inappropriate cutting parameters cause mechanical and thermal damages to the local host bone, which further lead to loosening of internal fixations. In this paper, the mechanistic models to predict the thrust forces and torques during bone drilling were developed, using a 3.20 mm diameter drill bit. As a procedure, the cutting action was investigated at three different regions of the drill point, namely cutting lips, secondary cutting edges and indentation zone. The models employed the analytical approach to account for the drill-bit geometry and cutting parameters, and an empirical approach to account for the material and friction properties. To complete the procedure, calibration experiments were conducted on bovine cortical femurs with two different spindle speeds (1000 and 3000 r/min) and feeds (0.03 and 0.06 mm/rev), and then the specific normal and friction coefficients were determined. The developed mechanistic models were validated with different ranges of parameters (500–3500 r/min speeds, and 0.02–0.07 mm/rev feeds) those commonly involved in manual and robot-assisted surgery. The validation study revealed that the thrust forces predicted using the mechanistic models showed a maximum error of only 5.80%. However, the torques predicted from the mechanistic model found with more error than the thrust forces. The predominant reasons for this under-prediction might because of the extrapolation used to determine the specific cutting pressures, slip-line field applied to the indentation zone instead of compressive fracture, and chip clogging involved during the bone drilling as demonstrated in earlier studies. Despite the deviations, the developed mechanistic models satisfactorily follow the trends of the thrust forces and torques experienced during bone drilling. The outcomes can be used to practice the bone drilling procedure and monitor the effect of process parameters on thrust forces and torques in the in-silico environment before performing actual surgery.

Background: Quantifying first ray mobility is crucial to understand aberrant foot biomechanics. A novel device (MAP1st) that can perform measurements of first ray mobility in different weightbearing conditions, foot alignments, and normalization was tested. The reliability of these measurement techniques was assessed in comparison to a handheld ruler considered representative of the common clinical examination. Methods: The study included 25 participants (50 feet). Two independent raters performed baseline, test-retest, and remove-replace measurements of first ray mobility with MAP1st and the handheld device. The effects of non-, partial, and full weightbearing in subtalar joint neutral and the resting calcaneal stance position were assessed. Measurement normalization relative to foot size was also investigated. Intra- and interclass correlation coefficients (ICCs) were calculated for each device between the 2 raters. In addition, Bland-Altman plots were constructed to determine if fixed biases or substantial outliers were present. Results: Similar intrarater ICC values were found for both devices (≥0.85). However, interrater ICC values were substantially improved by MAP1st compared with the handheld device (0.58 vs 0.06). Bland-Altman plots demonstrated biases of 1.27 mm for the handheld ruler, and 2.88 to 0.05 mm and −1.16 to 0.00 for linear and normalized MAP1st measurements, respectively. Improved reliability was achieved with MAP1st for normalized assessments of first ray mobility while the foot was placed in partial- and full-weightbearing resting calcaneal stance positions. Conclusion: MAP1st provided reliable assessments of partial- and full-weightbearing first ray mobility. It should help investigators to explore the potential relationships between first ray function and aberrant foot biomechanics in future research. Level of Evidence: Level II, prospective cohort study.

Ceiling fans are the most common equipment in any household with electricity to induce a higher air movement since the potential of natural ventilation is limited. However, the higher airflow region is generally limited to the zone below the fan. The non-uniform distribution of airflow is also affected by the furniture layout and airflow from window openings. This study attempts to evaluate the effect of the different window-opening patterns on the airflow inside naturally ventilated bedrooms, having a ceiling fan for air movement with numerical simulations and on-site measurements. The airflow pattern created by a ceiling fan in a room with furniture is modelled and simulated with ANSYS Fluent 2019 R3. The results were validated with on-site measurements and compared with the literature. The air velocity was measured in bedrooms of three different sizes. It was observed that the opening of windows created a better distribution of air irrespective of room size. The non-uniformity of the air velocity is reduced from 76% to 39% with the opening of windows in the larger-sized room. The reduction in non-uniformity is influenced by the location of windows also. The practice of opening windows along with the induced air movement by ceiling fans results in a better distribution of air in the space. Practical application: People tend to depend mainly on ceiling fans even if windows are open in naturally ventilated rooms. A study of patterns of non-uniform distribution of airflow can help designers to improve comfort conditions by specifying the number and location of fans and windows while designing room furniture layout. This aids the building services engineers to provide thermal comfort without always depending on alternative active ventilation strategies.

Considering the negative vertical dynamics effect of switched reluctance motor on an in-wheel motor driving system, this article presents a modeling and suppression method for unbalanced radial force of the in-wheel motor driving system. To tease out the coupling relationship within the in-wheel motor driving system, this investigation, respectively, explores the principle of unbalanced radial force and the coupling relationship between rotor eccentricity and road excitation based on the suspension response model with unbalanced radial force under road excitation. The switched reluctance motor nonlinear analytical model was fitted by the Fourier series, and its radial electromagnetic force was modeled and analyzed by the Maxwell stress tensor method. To mitigate the influence of radial electromagnetic force fluctuation and unbalanced radial force amplitude value under eccentricity condition on the in-wheel motor driving system, the elitist non-dominated sorting genetic algorithm was adopted to improve radial electromagnetic force fluctuation and unbalanced radial force amplitude value of the switched reluctance motor. The simulation results show that the proposed optimization method can suppress the radial electromagnetic force fluctuation and unbalanced radial force amplitude value, and the negative effect of vertical dynamics of the in-wheel motor driving system is conspicuously mitigated.

Based on non-affine models of hypersonic space vehicles, the tracking control problem of hypersonic vehicles is studied and analyzed in this article using funnel robust model-free control mechanism considering parametric uncertainty and external disturbances. First, the control system is decomposed into altitude subsystem and velocity subsystem. For altitude subsystem, we propose a concise funnel robust model-free control mechanism based on error driving, and a novel model transformation approach is applied to the controller design. The new model-free controller only contains a Hurwitz stable term and a filtering term, and does not need precise motion model and too much calculation, so it can improve the calculation speed of the system. For velocity subsystem, only a concise proportional-integral controller is needed to meet the tracking requirements. Moreover, the devised controller is capable of guaranteeing funnel performance on the altitude and velocity tracking errors. Finally, numerical simulation results are presented to verify the efficiency of the design.