Abstract
Performance of series connected batteries is limited by the "weakest link" effect, i.e., the cell or group of cells with the poorest performance in terms of temperature, power, or energy characteristics. To mitigate the "weakest link" effect, this study deals with the design, modeling, and experimental demonstration of a smart and hybrid balancing system (SHBS). A cell-to-cell shared energy transfer configuration is proposed, including a supercapacitor bank in the balancing bus, thus enabling hybridization. Energy is transferred from each battery module connected in series to the balancing bus, and vice-versa, by means of low-cost bi-directional dc-dc converters. The current setpoints of the converters are obtained by means of a smart balancing control strategy, implemented using convex optimization. The strategy is called "smart" because it pursues goals beyond the conventional state-of-charge equalization, including temperature and power capability equalization, and minimization of energy losses. Simulations show that the proposed SHBS is able to achieve all these goals effectively in an e-mobility application and are also used to assess the impact of different hybridization ratios and cooling conditions. Finally, an experimental setup is developed to demonstrate the feasibility of the SHBS.

Abstract
Switched reluctance machines (SRM) are simple, robust and fault tolerant machines, usually operating under strong nonlinear characteristics. Hence, modeling this machine is a most demanding task. While magnetic saturation is often addressed, hysteresis effect is usually disregarded. In order to include this phenomenon, an SRM drive simulation model was built, where magnetization characteristics are generated through the Jiles-Atherton (J-A) hysteresis model. SRM losses estimation is a challenging task, which demands continuous research efforts. This paper intends to investigate hysteresis impact on SRM copper losses. Due to the machine features, skin and proximity effects are considered. Different steady-state operation scenarios are simulated and compared.

Abstract
Switched reluctance machines (SRM) are simple, robust and fault tolerant machines, usually operating under strong nonlinear characteristics. Most SRM models address magnetic saturation, but hysteresis effect is usually disregarded. This paper is based on a developed four-quadrant SRM drive simulation model, where magnetization characteristics are generated through the original Jiles-Atherton (J-A) hysteresis model. The main goal is to investigate the hysteresis impact on the SRM drive controller performance. Steady-state operation scenarios are simulated and compared. For the adopted current control strategy (PWM), the results show a significant impact in all drive components, particularly for low speed with high load operation.

Abstract
This work focuses on hybrid balancing systems, a recently-proposed concept that enables balancing of battery cells and hybridization with supercapacitors. To control this system, a model predictive control framework is developed. In addition to distributing the supercapacitor power among the balancing circuits, this framework is also able to minimize state-of-charge and thermal imbalances in the battery cells, as well as energy losses in the balancing circuits. The effectiveness of the proposed approach is verified via numerical simulations. It is shown that, in comparison with state-of-art balancing solutions, the proposed control approach is able to decrease battery stress in up to 9% and the maximum temperature in up to 4.5%.

Abstract
It is common the use of the sonar technology in order acquire and posteriorly control the distance of an underwater vehicle towards an obstacle. Although this solution simplifies the problem and is effective in most cases, it might carry some disadvantages in certain underwater vehicles or conditions. In this work it is presented a system capable of controlling the altitude of an underwater vehicle using computer vision. The sensor capable of computing the distance is composed of a CCD camera and 2 green pointer lasers. Regarding the control of the vehicle, the solution used was based on the switching of two controllers, a velocity controller (based on a PI controller), and a position controller (based on a PD controller). The vehicle chosen to test the developed system was a profiler, which main task is the vertical navigation. The mathematical model was obtained and used in order to validate the controllers designed using the Simulink toolbox from Matlab. It was used a Kalman filter in order to have a better estimation of the state variables (altitude, depth, and velocity). The tests relative to the sensor developed responsible for the acquisition of the altitude showed an average relative error equal to 1 % in the range from 0 to 2.5 m. The UWsim underwater simulation environment was used in order to validate the integration of the system and its performance. © 2018 IEEE.

Abstract
Purpose This paper aims to present a mosaicking method for underwater robotic applications, whose result can be provided to other perceptual systems for scene understanding such as real-time object recognition. Design/methodology/approach This method is called robust and large-scale mosaicking (ROLAMOS) and presents an efficient frame-to-frame motion estimation with outlier removal and consistency checking that maps large visual areas in high resolution. The visual mosaic of the sea-floor is created on-the-fly by a robust registration procedure that composes monocular observations and manages the computational resources. Moreover, the registration process of ROLAMOS aligns the observation to the existing mosaic. Findings A comprehensive set of experiments compares the performance of ROLAMOS to other similar approaches, using both data sets (publicly available) and live data obtained by a ROV operating in real scenes. The results demonstrate that ROLAMOS is adequate for mapping of sea-floor scenarios as it provides accurate information from the seabed, which is of extreme importance for autonomous robots surveying the environment that does not rely on specialized computers. Originality/value The ROLAMOS is suitable for robotic applications that require an online, robust and effective technique to reconstruct the underwater environment from only visual information.