This paper presents a novel class 2 tensegrity robot which has contact between its rigid elements with a universal joint. Also, an strategy to obtain the forward and inverse position kinematic analysis using the parameters Denavit–Hartenberg in the distal convention is presented, obtaining the closed–form solution for the inverse position analysis and it was validated through simulation where a point of the robot followed the desired trajectory. Finally, the results were implemented in the experimental prototype of the novel class 2 tensegrity robot.

Nowadays, the use of renewable, green/eco-friendly technologies is attracting the attention of researchers, with a view to overcoming recent challenges that must be faced to guarantee the availability of Electric Vehicles (EVs). Therefore, this work proposes a methodology based on Genetic Algorithms (GA) and multivariate regression for estimating and modeling the State of Charge (SOC) in Electric Vehicles. Indeed, the proposal considers the continuous monitoring of six load-related variables that have an influence on the SOC (State of Charge), specifically, the vehicle acceleration, vehicle speed, battery bank temperature, motor RPM, motor current, and motor temperature. Thus, these measurements are evaluated in a structure comprised of a Genetic Algorithm and a multivariate regression model in order to find those relevant signals that better model the State of Charge, as well as the Root Mean Square Error (RMSE). The proposed approach is validated under a real set of data acquired from a self-assembly Electric Vehicle, and the obtained results show a maximum accuracy of approximately 95.5%; thus, this proposed method can be applied as a reliable diagnostic tool in the automotive industry.

In this paper, a new form-finding analysis methodology for a class 2 tensegrity robot is proposed. The methodology consists of two steps: first, the analysis of the possible geometric configurations of the robot is carried out through the results of the kinematic position analysis; and, second, from the static analysis, the equilibrium positions of the robot are found, which represents its workspace. Both kinematics and static analysis are resolved in a closed-form using basic tools of linear algebra instead of the strategies used in literature. Four numerical experiments are presented using the finite element analysis software ANSYS c . Additionally, a comparison between the results of the form-finding analysis methodology proposed and the ANSYS c results is presented.

Condition monitoring strategies play an important key role to ensure the proper operation and/or working conditions in electrical, mechanical, and electronic systems; in this sense, condition monitoring methods are commonly implemented aiming to avoid undesired breakdowns and are also implemented to extend the useful life of the evaluated elements as much as possible. Therefore, the objective of this work is to report the new trends and challenges related to condition monitoring strategies for assessing the state-of-charge in batteries under the Industry 4.0 framework. Specifically, this work is focused on the analysis of those signal processing and artificial intelligence techniques that are implemented in experimental and model-based assessing approaches. With this work, important aspects may be highlighted as well as the conclusions and prospects may be included for the development trend of condition monitoring strategies to assess and ensure the state-of-charge in batteries.

In this paper, a design of a vehicle called Human Powered Vehicle (HPV) will be developed, which must comply with the competition requirements of the ASME standard, since it has as purpose in the future to participate in the student competition organized by this association (ASME). In order to achieve compliance with the objectives of the vehicle design, a process was followed, in which the first step was to know the requirements that the model to be made must have, in accordance with the standard, that is, both in terms of form and materials to be used. Three different structures were made, which met the requirements of the model. These models were simulated with finite elements to determine their viability, which were subjected to various static loads, among which are loads due to overturning, impacts; Likewise, the fastenings to which the system is exposed were considered, these fastenings were considered of the fixed type. According to the results obtained, the model meets the needs of the ASME standard, in addition to being a light and safe vehicle for the driver.

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