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The study provides a numerical calculation for convection coefficients and heat fluxes due to aerodynamic heating on hypersonic vehicle which are obtained analytically and computationally for protection some thermal mechatronics systems. The heat transfer through a thin, a thick wall were analyzed in the present study. Convection coefficients and heat fluxes due to aerodynamic heating on critical surfaces of hypersonic vehicle are obtained analytically. The applicability of recovery temperature for axisymmetric configuration regions is discussed. Convection coefficient for the axisymmetric configuration region is obtained directly from axisymmetric region correlation. This paper shows and application of Crank-Nicolson scheme to solve numerically transient heat conduction problem conjugate with high speed aerodynamic heating problem. The results show good agreement with a known Lumped system method solution for a thin wall. Finally, it can use to the material design for the high speed flying body. [ABSTRACT FROM AUTHOR]

The issues like traffic congestion, parking space and vehicular emission can be reduced by adopting electric narrow tilting three-wheelers, which can also provide a cost-effective and safe mode of transport for low-income people. According to energy technology perspectives 2017, well-to-wheel global greenhouse gas emissions can be reduced up to 1.3 GtCO2-eq by 2060 by adopting electric mobility. This study presents a new and modified SDTC strategy and performance parameters that takes Road Bank Angle (RBA) into account so as to exhibit the adverse effects on rollover safety, ride comfort in terms of the perceived lateral acceleration and desired trajectory. Besides, this study identifies the importance of the RBA consideration in active tilt controlled vehicle for the scenario of parking on sloped surface. Simple electronic control architecture of the SDTC approach with real-time RBA consideration is proposed to address the limitations of SDTC and its supplementary advantages. This study evaluates the scenario of constant turn manoeuvre and vehicle parking on the banked roads. A multi-body model is used to capture the dynamic characteristics of the vehicle, whereas a characteristic of the Tilt Actuation System (TAS) and Active Steering (AS) system is incorporated in the form of a Transfer Function (TF) estimated using a system identification approach. The results indicate that the inclusion of a real-time RBA in the SDTC enables it to maintain steady-state torque and perceived lateral acceleration close to zero with the proposed controlled strategy, and it also keeps the vehicle upright on the sloped surface. It may be concluded that RBA compensation improves the ease of handling the vehicle while parking or riding on a sloped surface without significant control system alterations, which also makes it a viable alternative for physically disabled people. [ABSTRACT FROM AUTHOR]

This article aims to study the simulation and design of automobile automatic clutch under mechatronics. A new control strategy for the automatic clutch of the electromagnetic transmission is proposed. The clutch mechanism model, clutch drive model, clutch system model, and internal combustion engine model are constructed. The fuzzy logic control performance of the automatic clutch was verified in different operating modes, including starting on flat roads and mountain roads. The method provides a reasonable reference for the design of an automatic clutch of electromagnetic continuously variable transmission.

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paper presents a DSP-based design and control of a three-axis servo motion system that effectively divides control tasks between the master control terminal and four slave drives. The proposed architecture enhances the immediacy of platform positioning and the integration between software and hardware. The paper utilizes a high-accuracy encoder as a reference value for accuracy improvement and integrates firmware via the proposed embedded execution program, thereby reducing the accuracy error of the low-accuracy encoder. The main control core employs a digital signal processor (DSP) for input and output signal reading and writing, digital communication interface processing, and user interface. The slave controller utilizes four digital signal processors to accomplish servo position control in a digital way. The paper employs encoder calibration technology to upgrade the positioning accuracy of the surge axis. Finally, the paper validates the correctness and feasibility of the proposed method through experimental results from a set of adjustable experimental platforms of linear motion stroke and rotary motion stroke. In summary, the paper underscores the integration of hardware and software to attain high-precision and dependable control of the motion system. [ABSTRACT FROM AUTHOR]

Muscle tissue is prone to changes in composition and architecture following stroke. Changes in muscle tissue of the extremities are thought to increase resistance to muscle elongation or joint torque under passive conditions. These effects likely compound neuromuscular impairments, exacerbating movement function. Unfortunately, conventional rehabilitation is devoid of precise measures and relies on subjective assessments of passive joint torques. Shear wave ultrasound elastography, a tool to measure muscle mechanical properties, may be readily available for use in the rehabilitation setting as a precise measure, albeit at the muscle‐tissue level. To support this postulation, we evaluated the criterion validity of shear wave ultrasound elastography of the biceps brachii; we investigated its relationship with a laboratory‐based criterion measure for quantifying elbow joint torque in individuals with moderate to severe chronic stroke. Additionally, we evaluated construct validity, with the specific sub‐type of hypothesis testing of known groups, by testing the difference between arms. Measurements were performed under passive conditions at seven positions spanning the arc of elbow joint flexion‐extension in both arms of nine individuals with hemiparetic stroke. Surface electromyography was utilized for threshold‐based confirmation of muscle quiescence. A moderate relationship between the shear wave velocity and elbow joint torque was identified, and both metrics were greater in the paretic arm. Data supports the progression toward a clinical application of shear wave ultrasound elastography in evaluating altered muscle mechanical properties in stroke, while acknowledging that undetectable muscle activation or hypertonicity may contribute to the measurement. Shear wave ultrasound elastography may augment the conventional method of manually testing joint mobility by providing a high‐resolution precise value. Tissue‐level measurement may also assist in identifying new therapeutic targets for patient‐specific impairment‐based interventions. [ABSTRACT FROM AUTHOR]

In this study, a new dataset was created for use to estimate the state of charge (SOC) of lithium polymer batteries. A new experimental system was created to obtain the dataset by measuring the current, voltage, and temperature parameters of lithium polymer batteries. A convolutional neural network (CNN)-based deep learning model was used as the SOC prediction method. The effect of both batch size and dense network hyperparameter value on total parameter and deep learning error metric values for CNN-based lithium polymer battery SOC estimation is discussed. The proposed method, unlike deep learning models that require a high processing load in electronic cards, has provided remarkable results by being determined according to four different dense networks and two different batch size values. The proposed model has been obtained by performing experiments on optimizer, learning rate, dense network, and batch size values while determining the appropriate parameters to make successful predictions. The success of the CNN models was compared by conducting deep learning training on a computer with an Nvidia Gtx 1060 graphics card running the Ubuntu operating system. Adadelta optimizer achieved R2 0.977262 prediction success with learning rate 10–2, batch size 5 × 102, dense 105 hyperparameter values. According to the results of the experiment, it was concluded that in the CNN deep learning method, large dense layers and small batch size values created less error in SOC estimation. [ABSTRACT FROM AUTHOR]

Copyright of Automobile Technology is the property of Automobile Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, the design of a Digital-twin human-machine interface sensor (DT-HMIS) is proposed. This is a digital-twin sensor (DT-Sensor) that can meet the demands of human-machine automation collaboration in Industry 5.0. The DT-HMIS allows users/patients to add, modify, delete, query, and restore their previously memorized DT finger gesture mapping model and programmable logic controller (PLC) logic program, enabling the operation or access of the programmable controller input-output (I/O) interface and achieving the extended limb collaboration capability of users/patients. The system has two main functions: the first is gesture-encoded virtual manipulation, which indirectly accesses the PLC through the DT mapping model to complete control of electronic peripherals for extension-limbs ability by executing logic control program instructions. The second is gesture-based virtual manipulation to help non-verbal individuals create special verbal sentences through gesture commands to improve their expression ability. The design method uses primitive image processing and eight-way dual-bit signal processing algorithms to capture the movement of human finger gestures and convert them into digital signals. The system service maps control instructions by observing the digital signals of the DT-HMIS and drives motion control through mechatronics integration or speech synthesis feedback to express the operation requirements of inconvenient work or complex handheld physical tools. Based on the human-machine interface sensor of DT computer vision, it can reflect the user's command status without the need for additional wearable devices and promote interaction with the virtual world. When used for patients, the system ensures that the user's virtual control is mapped to physical device control, providing the convenience of independent operation while reducing caregiver fatigue. This study shows that the recognition accuracy can reach 99%, demonstrating practicality and application prospects. In future applications, users/patients can interact virtually with other peripheral devices through the DT-HMIS to meet their own interaction needs and promote industry progress. [ABSTRACT FROM AUTHOR]

Hydraulic and pneumatic control play an important role in mechatronic systems. Selection of control devices in designing mechatronic systems that uses hydraulic or pneumatic circuits studied by many researchers. A description of both hydraulic and pneumatic theory is introduces comparing between hydraulic and pneumatic systems based on their applications, used fluid, advantages and disadvantages and functions. Also, comparison between different power systems showing the difference between them in power source, cost, uses, affected parameters and advantages and disadvantages is studied. the importance of using hydraulic and pneumatic systems in different fields of industry is introduced. [ABSTRACT FROM AUTHOR]

Waste management is an essential component of urban management. As a waste solution, waste management is critical. The goal of this research is to develop a waste management database that is coupled with a mechatronic robot system. Compiling and gathering data on the sorts of garbage found in Indonesia is the starting point for this research. Indonesian waste is classified into six groups: cardboard, paper, metal, plastic, medical, and organic. The total images of the six groups are estimated at 1880 pictures. According to this picture database, Artificial Intelligence (AI) training was used to create the classification system. In the final AI process, the test method was performed using DenseNet121, DenseNet169, and DenseNet201. Testing using artificial intelligence DenseNet201 across 40 epochs yields the best 92,7% accuracy rate. Simultaneously with Artificial Intelligence testing, a mechatronic system is created as a direct implementation of the Artificial Intelligence output model. A four-servo arm robot with dc motor wheel mobility is included in the mechatronic system. According to these findings, the Indonesian waste database can be categorized correctly using Artificial Intelligence and the mechatronics system. This higher accuracy of the artificial intelligence model may be used to create a waste-sorting robot prototype. [ABSTRACT FROM AUTHOR]

In the automotive application for Electronic Control Units (ECU), dynamic models with high-precision to simulate mechatronic actuators are required for various analysis and design tasks like Hardware-in-the-Loop (HiL) simulation. It is known that the modeling of systems with significant friction effects is not accessible. The piecewise-affine (PWA) model has recently attracted considerable interest due to its high approximation capability for modeling systems with friction. Because the model quality depends intensely on the test signal design, a model-free optimized excitation signal design for identifying PWA models is presented in this paper. The presented method is demonstrated with an automotive throttle, and a PWA model is identified with a four-step identification approach. The result shows that the optimization method can achieve a better model quality, which is sufficient for the HiL simulation. [ABSTRACT FROM AUTHOR]

Advancing globalization and digitization are continuously changing the competitive conditions in the manufacturing industry. Globalization leads to an increasing number of competitors and results in the necessity for a stronger focus on individual customer needs. At the same time, digitization is leading to an expansion of mechanical products with components from the disciplines of electronics and software. This results in mechatronic products whose components generate a high degree of internal variety due to a large number of interdependencies, thus increasing the complexity of product development. By using modular product platforms, the variety of the products offered can be optimized. However, current approaches for developing modular product platforms are mainly designed for mechanical products, so that the consideration of interfaces between components from different disciplines is not taken into account comprehensively in module design. As a result, the consideration of further disciplines becomes necessary in module design in order to be able to optimize the internal and external variety of the products offered. Thus, this paper presents a concept for interdisciplinary module design in mechatronic modular product platforms. For this purpose, the individual components and their interfaces have to be identified and operationalized. Subsequently, the module design is optimized using a cluster algorithm. [ABSTRACT FROM AUTHOR]

Cascaded control structures are prevalent in industrial systems with many disturbances to obtain stable control but are cumbersome and challenging to tune. In this work, we propose cascaded constrained residual reinforcement learning (RL), an intuitive method that allows to improve the performance of a cascaded control structure while maintaining safe operation at all times. We draw inspiration from the constrained residual RL framework, in which a constrained reinforcement learning agent learns corrective adaptations to a base controller's output to increase optimality. We first revisit the interplay between the residual agent and the baseline controller and subsequently extend this to the cascaded case. We analyze the differences and challenges this structure brings and derive some principle insights from this into the stability and operation of the cascaded residual architecture. Next, we propose a novel actor structure to enable efficient learning under the cascaded setting. We show that the standard algorithm is suboptimal for application to cascaded control structures and validate our method on a high-fidelity simulator of a dual motor drivetrain, resulting in a performance improvement of 14.7% on average, with only a minor decrease in performance occurring during the training phase. We study the different principles constituting the method and examine and validate their contribution to the algorithm's performance under the considered cascaded control structure. [ABSTRACT FROM AUTHOR]

This paper introduces modular and context-aware evaporative cooling for the outdoor urban environment as a physical structure that could be implemented at various scales and physical contexts. We propose a technique for collecting occupancy and climatic data to create a computational context and optimise its operation. We then outline a concept for developing a predictive algorithm that would further enhance its performance. The research focuses on the interaction between the proposed system and the environment and establishes an evidence-based technique to balance the temperature drop and the humidity it generates. The study combines architectural design, mechanical engineering and computer science to enable the upscaled application of evaporative cooling to help reduce local heat accumulation in cities. [ABSTRACT FROM AUTHOR]

Paper [[21]] proposes an analytic solution for state-constrained optimal tracking control problems for continuous-time linear time-invariant (CT-LTI) systems based on model-based prediction, quadratic penalty function, and a variational approach. Special Issue Topics This Special Issue has received several submissions, out of which 13 contributions passed the review process and have been published. In recent years, research into the control of robotic and mechatronic systems has led to a wide variety of advanced paradigms and techniques, which have been extensively analysed and discussed in the scientific literature. Overall, the accepted papers illustrate a wide variety of alternative approaches and methods for improving the performance of mechatronic and robotic systems, with possible additional applications in related emerging fields, such as biomechanics. [Extracted from the article]

Copyright of Journal of Zhejiang University: Science A is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The infrastructure built in the 1950s has deteriorated beyond its service life. However, replacing all infrastructure is very difficult and involves huge replacement costs. To address this problem, the optimization of maintenance operations and participation of various stakeholders in the maintenance is required; however, maintenance technology and social cognition in terms of infrastructure deterioration remains insufficient. In this study, we perform research and development simultaneously to improve maintenance technology and social cognition. However, technological issues exist, such as lack of high-reliability diagnoses and optimized scheduling of maintenance, and optimized repair methods. In particular, this study focuses on high-reliability diagnosis. Next, communication of information between stakeholders and infrastructure is required to improve social cognition in terms of infrastructure deterioration. Particularly, in this study, the infrastructure with communication function between the residents and infrastructure is referred to as “future intelligent infrastructure.” We prototype a vibration-sensing-actuation device for a future intelligent infrastructure. In particular, we focus on the detection of the water main deterioration and estimation of the ground soil internal state. Then, the operation of the minimum valuable function is verified. The concept and fundamental functions of the vibration-sensing-actuation device are proposed. Moreover, a prototype device that functionally limits the active and dynamic sensing and simplifies autonomous discrimination is implemented for deterioration detection of the water main. Consequently, the fundamental operation of pipe-thinning detection is confirmed. Furthermore, an application for ground soil internal state estimation was considered. Consequently, the fundamental operation of detecting change in soil stiffness was confirmed.

In numerous industries e.g. oilfield pipelines, marine media, medicine and biomaterials microbially-induced corrosion (MIC) or biocorrosion has been universally identified. With improvements within the field of machine learning and artificial intelligence, the focal point is to generate hybrid advances that have superior exactness and unwavering quality. The traditional techniques of evaluation in generalized corrosion cannot be used to investigate the first steps of biocorrosion. Because in the first steps of MIC, the visible or detectable signs for biocorrosion early detection are not still available (e.g., time-consuming of microbiological culture. Therefore, novel methods such as biosensors, microfluidics, and mechatronics can be useful. In these methods, the possibility of data sharing, online/in-site monitoring, organizing of the smart clouds data and providing of Internet-of-Things linkages are strongly applicable. Here, a critically review performed on the literature introducing the quantitative and qualitative methods for detection and monitoring of microbial corrosion.

Assistive and rehabilitation technologies deal with solutions aiming at sustaining or enhancing individual’s capabilities and autonomy, thereby improving their overall welfare. In the framework of devices developed for daily life activities, we focus our attention on Sit-to-Stand (STS) devices, by proposing an innovative solution based on a mechanism that has been synthesized, designed, built and tested as a prototype version for accomplishing the task. The developed mechatronic system serves the requested motions of standing and sitting, possessing the main features of compactness and customization for being embedded in chairs and conventional seats, according to a procedure that will be detailed in the paper. A simulation in a realistic scenario using a 3D model of an individual was carried out to size and verify the mechanical design and actuation. The mechatronic design of the system and its operations were reported using a laboratory prototype to show its engineering soundness and first experimental tests.

This article presents an open-source device illustrating the well-known magnetic levitation experiment. The uniqueness of this particular device lies in its exceptionally small dimensions, affordability and availability, which makes it a perfect design for take-home experiments for education but it can also serve as a referential design for testing various control algorithms in research. In addition, this paper provides a comprehensive hardware design for reproducibility along with the detailed derivation of the mathematical model, system identification and validation. Moreover, the introduced hardware comes with an easy-to-use open-source application programming interface in C/C++ for the Arduino IDE, Simulink and CircuitPython. REXYGEN, another environment similar to Simulink, had also been used to demonstrate the capabilities of the MagnetoShield.

Lithium-ion batteries have revolutionized the portable and stationary energy industry and are finding widespread application in sectors such as automotive, consumer electronics, renewable energy, and many others. However, their efficiency and longevity are closely tied to accurately measuring their SOC and state of health (SOH). The need for precise algorithms to estimate SOC and SOH has become increasingly critical in light of the widespread adoption of lithium-ion batteries in industrial and automotive applications. While the benefits of lithium-ion batteries are undeniable, the challenges related to their efficient and safe management cannot be overlooked. Accurate estimation of SOC and SOH is crucial for ensuring optimal battery management, maximizing battery lifespan, optimizing performance, and preventing sudden failures. Consequently, research and development of reliable algorithms for estimating SOC and SOH have become an area of growing interest for the scientific and industrial community. This review article aims to provide an in-depth analysis of the state-of-the-art in SOC and SOH estimation algorithms for lithium-ion batteries. The most recent and promising theoretical and practical techniques used to address the challenges of accurate SOC and SOH estimation will be examined and evaluated. Additionally, critical evaluation of different approaches will be highlighted: emphasizing the advantages, limitations, and potential areas for improvement. The goal is to provide a clear view of the current landscape and to identify possible future directions for research and development in this crucial field for technological innovation.