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In reversible protonic ceramic cells (RPCCs), due to their fast oxygen reaction kinetics, perovskite-structured cathode materials have been in the spotlight up to this point. However, such materials have some drawbacks such as low phase stability in humid atmospheres, high thermal expansion coefficient, and relatively low proton conductivity despite high electrocatalytic activities when used as steam-air electrodes. Hence, we suggest that novel misfit-layered structure Ca3Co4O9+δ (CCO)-based materials be used to overcome these technical issues with superior performance in RPCCs. Although CCO is a cobaltite-material, CCO has a similar thermal expansion coefficient as BZCYYb electrolyte’s (10‒12×10-6 K-1). Moreover, the plate-like morphology of the CCO-based materials are favorable for the introduction or emission of steam. Further, with alkali metal doping in Ca-site, CCO generates extra charge carrier species with the modified Co oxidation state, which results in high proton uptake and diffusion mechanism. Altogether, 5 mol% potassium-doped CCO-cells show great potential as a cathode material.

Background: Wearable devices for robot-assisted gait training (RAGT) provide overground gait training for the rehabilitation of neurological injuries. We aimed to evaluate the effectiveness and safety of RAGT in patients with a neurologic deficit. Methods: Twenty-eight patients receiving more than ten sessions of overground RAGT using a joint-torque-assisting wearable exoskeletal robot were retrospectively analyzed in this study. Nineteen patients with brain injury, seven patients with spinal cord injury and two patients with peripheral nerve injury were included. Clinical outcomes, such as the Medical Research Council scale for muscle strength, Berg balance scale, functional ambulation category, trunk control tests, and Fugl–Meyer motor assessment of the lower extremities, were recorded before and after RAGT. Parameters for RAGT and adverse events were also recorded. Results: The Medical Research Council scale scores for muscle strength (36.6 to 37.8), Berg balance scale (24.9 to 32.2), and functional ambulation category (1.8 to 2.7) significantly improved after overground RAGT (p < 0.05). The familiarization process was completed within six sessions of RAGT. Only two mild adverse events were reported. Conclusions: Overground RAGT using wearable devices can improve muscle strength, balance, and gait function. It is safe in patients with neurologic injury.

In the permanent magnet synchronous motor (PMSM) sensorless drive method, motor inductance is a decisive parameter for rotor position estimation. Due to core magnetic saturation, the motor current easily invokes inductance variation and degrades rotor position estimation accuracy. For a constant load torque, saturated inductance and inductance error in the sensorless drive method are constant. Inductance error results in constant rotor position estimation error and minor degradations, such as less optimal torque current, but no speed estimation error. For a periodic load torque, the inductance parameter error periodically fluctuates and, as a result, the position estimation error and speed error also periodically fluctuate. Periodic speed error makes speed regulation and load torque compensation especially difficult. This paper presents an inductance parameter estimator based on polynomial neural network (PNN) machine learning for PMSM sensorless drive with a period load torque compensator. By applying an inductance estimator, we also proposed a magnetic saturation compensation method to minimize periodic speed fluctuation. Simulation and experiments were conducted to validate the proposed method by confirming improved position and speed estimation accuracy and reduced system vibration against periodic load torque.

AC motors have been used in many applications owing to their wide speed range and their high efficiency. However, the maximum speed of the AC motor is limited by the back electromotive force(BEMF) which is determined by the mechanical parameter of a machine. By using the field-weakening control, it can be controlled above the base-speed, but this method also has its limitation. To extend a speed-range of machine under operation, the studies on the methods of changing mechanical elements that affect the BEMF have been conducted. The mechanical elements which affect the BEMF are number of poles, connection method, and the number of the turns in the winding changeover method. The conventional change over method of the number of the turns requires switch box with diode bridges and a snubber capacitor [7], [8]. These methods could generate the torque ripple by the long transient time occurred by winding-changeover circuit. In this paper, a novel method is proposed to complement the problems of power transmission and torque ripple without the need of the switch box. The experimental results show the reduced transient time when the winding is changed also show that no power transmission occurs since this method does not use the diode bridges and a snubber capacitor.

This paper presents a dynamic modeling, simulation, and analysis of a Battery Electric Vehicle (BEV) according to vehicle dynamic characteristics. Mathematical model variants for the components of BEVs can be modeled and investigated using the Matlab/Simulink software. In order to compare the dynamic performance of BEVs under inverter fault and normal conditions, the CarSim co-simulation platform is configured with real vehicle calibration data. Using this approach, it was possible to quickly check for dynamic performance issues of an electric vehicle without incurring the time delay and cost. The simulation results such as motor output, vehicle speed/acceleration, and propulsion forces are discussed and compared for each drive mode.