The rapidly growing deployment of Electric Vehicles (EV) put strong demands on the development of Lithium-Ion Batteries (LIBs) but also into its dismantling process, a necessary step for circular economy. The aim of this study is therefore to develop an autonomous task planner for the dismantling of EV Lithium-Ion Battery pack to a module level through the design and implementation of a computer vision system. This research contributes to moving closer towards fully automated EV battery robotic dismantling, an inevitable step for a sustainable world transition to an electric economy. For the proposed task planner the main functions consist in identifying LIB components and their locations, in creating a feasible dismantling plan, and lastly in moving the robot to the detected dismantling positions. Results show that the proposed method has measurement errors lower than 5 mm. In addition, the system is able to perform all the steps in the order and with a total average time of 34 s. The computer vision, robotics and battery disassembly have been successfully unified, resulting in a designed and tested task planner well suited for product with large variations and uncertainties.
This research paper presents the first part of a comparative analysis of a novel self-contained electro-hydraulic cylinder with passive load-holding capability against a state of the art, valve-controlled actuation system that is typically used in load-carrying applications. The study is carried out on a single-boom crane with focus on the control design and motion performance analysis. First, a model-based design approach is carried out to derive the control parameters for both actuation systems using experimentally validated models. The linear analysis shows that the new drive system has higher gain margin, allowing a considerably more aggressive closed-loop position controller. Several benefits were experimentally confirmed, such as faster rise time, 75% shorter settling time, 61% less overshoot, 66% better position tracking, and reduction of pressure oscillations. The proposed control algorithm is also proven to be robust against load variation providing essentially the same position accuracy. In conclusion, the novel self-contained system is experimentally proven to be a valid alternative to conventional hydraulics for applications where passive load-holding is required.
The main contribution of the paper is the development of an adaptive backstepping controller for a nonlinear hydraulic-mechanical system considering valve dynamics. The paper also compares the performance of two variants of an adaptive backstepping tracking controller with a simple PI controller. The results show that the backstepping controller considering valve dynamics achieves significantly better tracking performance than the PI controller, while handling uncertain parameters related to internal leakage, friction, the orifice equation and oil characteristics.
This article presents a survey on actuation systems encountered in offshore drilling applications. Specifically, it focuses on giving a comparison of hydraulic and electric drivetrains along with detailed explanations of their advantages and drawbacks. A significant number of industrial case studies is examined in addition to the collection of academic publications, in order to accurately describe the current market situation. Some key directions of research and development required to satisfy increasing demands on powertrains operating offshore are identified. The impact of the literature and application surveys is further strengthened by benchmarking two designs of a full-scale pipe handling machine. Apart from other benefits, the electrically actuated machine reduces the total power consumption by 70 % compared to its hydraulically driven counterpart. It is concluded that electric actuation systems, among other advantages, in general offer higher efficiency and flexibility, however, in some specific applications (such as energy accumulation or translational motion control) hydraulic powertrains are favorable.
Abstract. In this paper, we present a new approach for detecting potentially damaging European winter windstorms from a multi-variable perspective. European winter windstorms being usually associated with extra-tropical cyclones (ETCs), there is a coupling between the intensity of the surface wind speeds and other meso-scale and large-scale features characteristic of ETCs. Here we focus on the relative vorticity at 850 hPa and the sea level pressure anomaly, which are also used in ETC detection studies, along with the ratio of the 10 m wind speed to its 98th percentile. When analysing 10 events known by the insurance industry to have caused extreme damages, we find that they share an intense signature in each of the 3 fields. This shows that the relative vorticity and the mean sea level pressure have a predictive value of the intensity of the generated windstorms. The 10 major events are not the most intense in any of the 3 variables considered separately, but we show that the combination of the 3 variables is an efficient way of extracting these events from a reanalysis data set.
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