A Novel Algorithm for Hydrostatic-Mechanical Mobile Machines with a Dual-Clutch Transmission

Mobile machines using a hydrostatic transmission is highly efficient under lower working-speed condition but less capable at higher transport velocities. To enhance overall efficiency, we have improved the powertrain design by combining a hydrostatic transmission with a dual-clutch transmission (DCT). Compared with other mechanical gearboxes, the DCT avoids the interruption of torque transmission in the process of shifting without sacrificing more transmission efficiency. However, there are some problems of unstable torque transmission during the shifting process, and an excessive torque drop occurring at the end of the gear shift, which result in a poor drive comfort. To enhance the performance of the novel structural possibility of powertrain design, we designed a novel control strategy, which maintains the sliding in the torque phase and reduces the difference before and after the engagement, for the motor torque and the clutch torques during the shifting process, and then validated the control effect with model-based simulation. As a result, the control strategy employing clutch and motor torque control achieve a smooth shifting process since the drive torque is well tracked, and highly dynamical actuators are not required. As another benefit, only two calibration parameters are designed and actually needed to adjust the control performance systematically, even for any different sizes machines. Our research indicates the possibility to adopt dual-clutch in the field of construction machines

Influence of Architecture Design on the Performance and Fuel Efficiency of Hydraulic Hybrid Transmissions

Hydraulic hybrids are a proven and effective alternative to electric hybrids for increasing the fuel efficiency of on-road vehicles. To further the state-of-the-art this work investigates how architecture design influences the performance, fuel efficiency, and controllability of hydraulic hybrid transmissions. To that end a novel neural network based power management controller was proposed and investigated for conventional hydraulic hybrids. This control scheme trained a neural network to generalize the globally optimal, though non-implementable, state trajectories generated by dynamic programming. Once trained the neural network was used for online prediction of a transmission’s optimal state trajectory during untrained cycles forming the basis of an implementable controller. During hardware-in-the-loop (HIL) testing the proposed control strategy improved fuel efficiency by up to 25.5% when compared with baseline approaches. To further improve performance and fuel efficiency a novel transmission architecture termed a Blended Hydraulic Hybrid was proposed and investigated. This novel architecture improves on existing hydraulic hybrids by partially decoupling power transmission from energy storage while simultaneously providing means to recouple the systems when advantageous. Optimal control studies showed the proposed architecture improved fuel efficiency over both baseline mechanical and conventional hydraulic hybrid transmissions. Effective system level and supervisory control schemes were also proposed for the blended hybrid. In order to investigate the concept’s feasibility a blended hybrid transmission was constructed and successfully tested on a HIL transmission dynamometer. Finally to investigate controllability and driver perception an SUV was retrofitted with a blended hybrid transmission. Successful on-road vehicle testing showcased the potential of this novel hybrid architecture as a viable alternative to more conventional electric hybrids in the transportation sector

Fast CRDNN: Towards on Site Training of Mobile Construction Machines

The CRDNN is a combined neural network that can increase the holistic efficiency of torque based mobile working machines by about 9% by means of accurately detecting the truck loading cycles. On the one hand, it is a robust but offline learning algorithm so that it is more accurate and much quicker than the previous methods. However, on the other hand, its accuracy can not always be guaranteed because of the diversity of the mobile machines industry and the nature of the offline method. To address the problem, we utilize the transfer learning algorithm and the Internet of Things (IoT) technology. Concretely, the CRDNN is first trained by computer and then saved in the on-board ECU. In case that the pre-trained CRDNN is not suitable for the new machine, the operator can label some new data by our App connected to the on-board ECU of that machine through Bluetooth. With the newly labeled data, we can directly further train the pretrained CRDNN on the ECU without overloading since transfer learning requires less computation effort than training the networks from scratch. In our paper, we prove this idea and show that CRDNN is always competent, with the help of transfer learning and IoT technology by field experiment, even the new machine may have a different distribution. Also, we compared the performance of other SOTA multivariate time series algorithms on predicting the working state of the mobile machines, which denotes that the CRDNNs are still the most suitable solution. As a by-product, we build up a human-machine communication system to label the dataset, which can be operated by engineers without knowledge about Artificial Intelligence (AI).Comment: 15 pages, 18 figure

Volume 3 – Conference

We are pleased to present the conference proceedings for the 12th edition of the International Fluid Power Conference (IFK). The IFK is one of the world’s most significant scientific conferences on fluid power control technology and systems. It offers a common platform for the presentation and discussion of trends and innovations to manufacturers, users and scientists. The Chair of Fluid-Mechatronic Systems at the TU Dresden is organizing and hosting the IFK for the sixth time. Supporting hosts are the Fluid Power Association of the German Engineering Federation (VDMA), Dresdner Verein zur Förderung der Fluidtechnik e. V. (DVF) and GWT-TUD GmbH. The organization and the conference location alternates every two years between the Chair of Fluid-Mechatronic Systems in Dresden and the Institute for Fluid Power Drives and Systems in Aachen. The symposium on the first day is dedicated to presentations focused on methodology and fundamental research. The two following conference days offer a wide variety of application and technology orientated papers about the latest state of the art in fluid power. It is this combination that makes the IFK a unique and excellent forum for the exchange of academic research and industrial application experience. A simultaneously ongoing exhibition offers the possibility to get product information and to have individual talks with manufacturers. The theme of the 12th IFK is “Fluid Power – Future Technology”, covering topics that enable the development of 5G-ready, cost-efficient and demand-driven structures, as well as individual decentralized drives. Another topic is the real-time data exchange that allows the application of numerous predictive maintenance strategies, which will significantly increase the availability of fluid power systems and their elements and ensure their improved lifetime performance. We create an atmosphere for casual exchange by offering a vast frame and cultural program. This includes a get-together, a conference banquet, laboratory festivities and some physical activities such as jogging in Dresden’s old town.:Group 8: Pneumatics Group 9 | 11: Mobile applications Group 10: Special domains Group 12: Novel system architectures Group 13 | 15: Actuators & sensors Group 14: Safety & reliabilit

Investigation of Novel Displacement-Controlled Hydraulic Architectures for Railway Construction and Maintenance Machines

This dissertation aims at showing how to transform hydraulic systems of railway multi-actuator machinery characterized by inefficient state-of-the-art systems into the 21st Century. Designing machines that are highly efficient, productive, reliable, and cost affordable represents the target of this research. In this regard, migrating from valve-controlled architectures to displacement-controlled layouts is the proper answer. Displacement-controlled systems remove the losses generated by flow throttling typical of conventional circuits, allow an easy implementation of energy recovery (e.g. during regenerative braking), and create the possibility for the use of hybrid systems capable of maximizing the downsizing of the combustion engine. One portion of the dissertation focuses on efficient propulsion systems suitable for railway construction and maintenance machines. Two non-hybrid architectures are first proposed, i.e. a novel layout grounded on two independent hydrostatic transmissions (HSTs) and two secondary controlled hydraulic motors (SCHMs) connected in parallel. Three suitable control strategies are developed according to the specific requirements for railway machines and dedicated controllers are implemented. Detailed analyses are conducted via high-fidelity virtual simulations involving accurate modeling of the rail/wheel interface. The performance of the propulsion systems is proven by acceptable velocity tracking, accurate stopping position, achieving regenerative braking, and the expected behavior of the slip coefficients on both axles. Energy efficiency is the main emphasis during representative working cycles, which shows that the independent HSTs are more efficient. They consume 6.6% less energy than the SCHMs working with variable-pressure and 12.8% less energy than the SCHMs controlled with constant-pressure. Additionally, two alternative hybrid propulsion systems are proposed and investigated. These architectures enable a 35% reduction of the baseline machine’s rated engine power without modifying the working hydraulics. Concerning the working hydraulics, the focus is to extend displacement-controlled technology to specific functions on railway construction and maintenance machines. Two specific examples of complete hydraulic circuits for the next generation tamper-liners are proposed. In particular, an innovative approach used to drive displacement-controlled dual function squeeze actuators is presented, implemented, and experimentally validated. This approach combines two functions into a unique actuator, namely squeezing the ballast and vibrating the tamping tools of the work-heads. This results in many advantages, such as variable amplitude and variable frequency of the tamping tools’ vibration, improved reliability of the tamping process, and energy efficient actuation. A motion of the squeeze actuator characterized by a vibration up to 45 Hz, i.e. the frequency used in state-of-the-art systems, is experimentally confirmed. In conclusion, this dissertation demonstrates that displacement-controlled actuation represents the correct solution for next-generation railway construction and maintenance machines

Conception et évaluation d'actionneurs à embrayages magnétorhéologiques pour la robotique collaborative

La robotique collaborative se démarque de la robotique industrielle par sa sécurité dans le but de travailler en collaboration avec les humains. Toutefois, la majorité des robots collaboratifs sériels reposent sur un actionnement à haut ratio de réduction, ce qui augmente considérablement la masse reflétée à l’effecteur du robot, et donc, nuit à la sécurité. Pour pallier cette masse reflétée et maintenir un seuil minimal de sécurité, les vitesses d’opération sont abaissées, nuisant ainsi directement à la productivité des entreprises. Afin de minimiser la masse reflétée à l’effecteur, les masses des actionneurs ainsi que leur inertie reflétée doivent être minimisés. Les embrayages à fluide magnétorhéologique (MR) maintenus en glissement continus découplent l’inertie provenant de la source de puissance, souvent un moteur et un réducteur, offrant ainsi un actionneur possédant un haut rapport couple-inertie. Toutefois, les embrayages MR, utilisés de façon antagoniste, ajoutent des composantes à l’actionneur ce qui réduit la densité de couple, et donc, augmente la masse reflétée à l’effecteur du robot. Certains actionneurs MR [1–3] ont été développés, mais leur basse densité de couple contrebalance leur faible inertie lorsqu’utilisés comme actionneurs aux articulations de robots collaboratifs sériels. Cette constatation a mené à ma question de recherche : Comment profiter de la faible inertie des actionneurs MR pour maximiser les performances dynamiques des robots collaboratifs sériels? L’objectif de ce projet de recherche vise donc à étudier le potentiel des embrayages MR en robotique collaborative. Pour ce faire, deux architectures MR sont développées et testées expérimentalement. La première architecture consiste en une articulation robotisée modulaire comportant des embrayages MR en glissement continu et possédant un rapport couple/masse et une taille équivalente à l’actionneur d’Universal Robots (UR) de couple égal, mais possédant un rapport couple/inertie 150 fois supérieur. À l’intérieur de l’articulation, deux chaines de puissance (2 moteurs et 2 embrayages MR) indépendantes se rejoignent à la sortie du joint offrant ainsi une redondance et augmentant la densité de couple comparativement à une architecture standard (1 moteur pour 2 embrayages MR). La deuxième architecture étudiée consiste en un actionnement délocalisé du robot où les embrayages MR sont situés à la base du robot et une transmission hydrostatique à membranes déroulantes achemine la puissance aux articulations. Cette architecture a été testée expérimentalement dans un contexte de bras robotisé surnuméraire. Contrairement à l’articulation MR, cette architecture n’offre pas une modularité habituellement recherchée en robotique sérielle, mais offre la possibilité de réduire l’inertie de la structure avec la délocalisation de l’actionnement. Finalement, les deux architectures développées ont été comparées à une architecture standard (haut ratio avec réducteur harmonique) afin de situer le potentiel du MR en robotique collaborative. Cette analyse théorique a démontré que pour un robot collaboratif sériel à 6 degrés de liberté, les architectures MR ont le potentiel d’accélérer 6 et 3 fois plus (respectivement) que le robot standard d’UR, composé d’actionneurs à hauts ratios

Volume 2 – Conference: Wednesday, March 9

10. Internationales Fluidtechnisches Kolloquium:Group 1 | 2: Novel System Structures Group 3 | 5: Pumps Group 4: Thermal Behaviour Group 6: Industrial Hydraulic

AI and IoT Meet Mobile Machines: Towards a Smart Working Site

Infrastructure construction is society's cornerstone and economics' catalyst. Therefore, improving mobile machinery's efficiency and reducing their cost of use have enormous economic benefits in the vast and growing construction market. In this thesis, I envision a novel concept smart working site to increase productivity through fleet management from multiple aspects and with Artificial Intelligence (AI) and Internet of Things (IoT)