Load-dependent Variable Gearing Mechanism of Muscle-like Soft Actuator

Pennate muscle is characterized by muscle fibers that are oriented at a certain angle (pennation angle) relative to the muscle’s line of action and rotation during contraction. This fiber rotation amplifies the shortening velocity of muscle, to match loading conditions without any control system. This unique variable gearing mechanism, which characterized by Architecture Gear Ratio (AGR), is involves complex interaction among three key elements: muscle fibers, connective tissue, and the pennation angle. However, how three elements determine the AGR of muscle-like actuator is still unknown. This study introduces a Himisk actuator that arranges five contractile units at a certain pennation angle in a flexible matrix, the experiment and simulation results demonstrated that the proposed actuator could vary AGR automatically in response to variable loading conditions. Based on this actuator, we present a series of actuators by simulations with the varying pennation angle (P), elastic modulus of the flexible matrix (E), and number of contractile units (N) to analyze their effects on AGR, and their interaction by three-factor analysis of variance. The results demonstrated that P and N effect on the AGR significantly, while E effects on AGR slightly, which supported the idea that the P is the essential factor for the AGR, and N is also an important factor due to the capability of force generation. This provides a better understanding of mechanical behavior and an effective optimizing strategy to muscle-like soft actuator.

Estimating the Remaining Useful Life of Proton Exchange Membrane Fuel Cells under Variable Loading Conditions Online

The major challenges for the commercialization of proton exchange membrane fuel cells (PEMFCs) are durability and cost. Prognostics and health management technology enable appropriate decisions and maintenance measures by estimating the current state of health and predicting the degradation trend, which can help extend the life and reduce the maintenance costs of PEMFCs. This paper proposes an online model-based prognostics method to estimate the degradation trend and the remaining useful life of PEMFCs. A non-linear empirical degradation model is proposed based on an aging test, then three degradation state variables, including degradation degree, degradation speed and degradation acceleration, can be estimated online by the particle filter algorithm to predict the degradation trend and remaining useful life. Moreover, a new health indicator is proposed to replace the actual variable loading conditions with the simulated constant loading conditions. Test results using actual aging data show that the proposed method is suitable for online remaining useful life estimation under variable loading conditions. In addition, the proposed prognostics method, which considers the activation loss and the ohmic loss to be the main factors leading to the voltage degradation of PEMFCs, can predict the degradation trend and remaining useful life at variable degradation accelerations.

Speed control of universal motor

Universal Motors (UM) are normally used for driving portable apparatus such as hand tool machines, vacuum cleaners and most domestic apparatus. The importance of UM is due to its own advantages such as high starting torque, very powerful in relation to its small size, having a variable speed; and lower cost. So, this paper focus on UM speed control under variable loading conditions. A mathematical model for UM is designed. Two controllers are proposed for controlling the motor speed, output rate controller and output reset controller. Ant Colony Optimization (ACO) is proposed for tuning the controller’s parameters due to its impact on solving different optimization problems. It possesses fast convergence, minimum algorithm parameters required, lower consecution time and give optimal results without needing large number of iterations. The results are compared and discussed accurately, which show the proposed tuning technique work well and give optimal results for both controllers.