Battery state of health (SoH) is an important parameter of the battery's ability to store and deliver electrical energy. Various methods have been so far developed to calculate the battery SoH, such as through the calculation of battery impedance or battery capacity using Kalman Filter, Fuzzy theory, Probabilistic Neural Network, adaptive hybrid battery model, and Double Unscented Kalman Filtering (D-UKF) algorithm. This paper proposes an approach to estimate the value of battery SoH based on the charging time measurement. The results of observation and measurements showed that a new and used batteries would indicate different charging times. Unhealthy battery tends to have faster charging and discharging time. The undertaken analysis has been focused on finding out the relationship between the battery SoH and the charging time range. To validate the results of this proposed approach, the use of battery capacity method has been considered as comparison. It can be concluded that there is a strong correlation between the two discussed SoH estimation methods, confirming that the proposed method is feasible as an alternative SoH estimation method to the widely known battery capacity method. The correlation between the charging-disharging times of healthy and unhealthy batteries is very prospective to develop a battery charger in the future with a prime advantage of not requiring any sensor for the data acquisition.

As the main testbed platform of Artificial Intelligence, the robot plays an essential role in creating an environment for industrial revolution 4.0. According to their bases, the robot can be categorized into a fixed based robot and a mobile robot. Current robotics research direction is interesting since people strive to create a mobile robot able to move in the land, water, and air. This paper presents development of a quadruped mobile robot and its movement system using geometric-based inverse kinematics. The study is related to the movement of a four-legged (quadruped) mobile robot with three Degrees of Freedom (3 DOF) for each leg. Because it has four legs, the movement of the robot can only be done through coordinating the movements of each leg. In this study, the trot gait pattern method is proposed to coordinate the movement of the robot's legs. The end-effector position of each leg is generated by a simple trajectory generator with half rectified sine wave pattern. Furthermore, to move each robot's leg, it is proposed to use geometric-based inverse kinematic. The experimental results showed that the proposed method succeeded in moving the mobile robot with precision. Movement errors in the translation direction are 1.83% with the average pose error of 1.33 degrees, means the mobile robot has good walking stability.

No abstract

No abstract

No abstract