The present study proposes a new parameter estimation technique for undefined parameters of proton exchange membrane fuel cell (PEMFC) stack models. To provide an efficient model identifier, an objective function by the Sum of Squared Error (SSE) between the empirical data and the predicted date of the PEM fuel cell stack has been employed, and the aim is to minimize this objective function. Here, a new improved design of Remora Optimizer is designed and used for the minimization purpose. The improved method has been improved by self-adaptive weighting for improving the convergence rate and for providing promising balance searching in both initial and next steps, and chaos mechanism for increasing the optimization process while keeping the exploration term based on pseudorandom values. The technique is used in two test cases and then a comparison of the results with several newest techniques is performed. Simulation results showed that the proposed IROA method with 2.05% and 0.019% error ratio for NedSstack PS6 and Horizon 500W PEMFC stack models, respectively, provides the best results compared with other comparative methods. Simulation achievements indicate that the presented approach has higher efficiency than the other compared methods.

Affected by the magnetic saturation effect and unmodeled dynamics, the parameters of the synchronous reluctance motor (SynRM) are highly nonlinear and time-varying. The resulting unreasonable current loop reference command severely restricts the maximum efficiency and high control performance of SynRM. Therefore, an adaptive non-singular terminal sliding mode control scheme for SynRM drive system is proposed to improve the dynamic performance and robustness. Firstly, an analytical model of flux linkage and inductance that satisfies the energy conversion mechanism is proposed to estimate the required parameters of the control system in real time. Secondly, a novel fast finite time adaptive-gain reaching law is proposed to shorten the arrival time while reducing the chatter near the sliding mode surface. Then, a non-linear disturbance observer is designed to estimate the total disturbance of the system. The asymptotic stability of the system is proved by Lyapunov's theorem. The experimental results demonstrate that the system has satisfactory dynamic performance and robustness.

In the face of growing environmental pollution, developing a fuel-cell-driven shunting locomotive is a great challenge in China for environmental protection and energy saving, which combines the environmental advantages of an electric locomotive with the lower infrastructure costs of a diesel-electric locomotive. In this paper, the investigation status and the development trend of the fuel-cell-driven shunting locomotive were introduced. Through innovation of the power system using fuel cells, an experiment prototype of a fuel-cell shunting locomotive was developed, which would reduce the effects on the environment of the existing locomotives. This was the first locomotive to use a proton exchange membrane fuel-cell (PEMFC) power plant in China. From October 2012, we started to test the fuel-cell power plant and further test runs on the test rail-line in Chengdu, Sichuan. The achieved encouraging results can provide fundamental data for the modification of the current individual fuel cell locomotives or further development of the fuel-cell hybrid ones in China.