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.

This research paper presents the second 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 hydraulic system that is typically used in load-carrying applications. After addressing the control design and motion performance in the first part of the study, the comparison is now focused on the systems’ energy efficiency. It is experimentally shown that the self-contained solution enables 62% energy savings in a representative working cycle due to its throttleless and power-on-demand nature. In the self-contained drive, up to 77% of the energy taken from the power supply can be used effectively if the recovered energy is reused, an option that is not possible in the state of the art hydraulic architecture. In fact, more than 20% of the consumed energy may be recovered in the self-contained system during the proposed working cycle. In summary, the novel self-contained option is experimentally proven to be a valid alternative to conventional hydraulics for applications where passive load-holding is required both in terms of dynamic response and energy consumption. Introducing such self-sufficient and completely sealed devices also reduces the risk of oil spill pollution, helping fluid power to become a cleaner technology.

This paper presents a robust model-based technique to detect multiple faults in permanent magnet synchronous motors (PMSMs), namely inter-turn short circuit (ITSC) and encoder faults. The proposed model is based on a structural analysis, which uses the dynamic mathematical model of a PMSM in an $abc$ frame to evaluate the system’s structural model in matrix form. The just-determined and over-determined parts of the system are separated by a Dulmage–Mendelsohn decomposition tool. Subsequently, the analytical redundant relations obtained using the over-determined part of the system are used to form smaller redundant testable sub-models based on the number of defined fault terms. Furthermore, four structured residuals are designed based on the acquired redundant sub-models to detect measurement faults in the encoder and ITSC faults, which are applied in different levels of each phase winding. The effectiveness of the proposed detection method is validated by an in-house test setup of an inverter-fed PMSM, where ITSC and encoder faults are applied to the system in different time intervals using controllable relays. Finally, a statistical detector, namely a generalized likelihood ratio test algorithm, is implemented in the decision-making diagnostic system resulting in the ability to detect ITSC faults as small as one single short-circuited turn out of 102, i.e., when less than 1% of the PMSM phase winding is short-circuited.