Compared to conventional vehicles Hybrid Electric Vehicles (HEVs) provide fairly high fuel economy with lower emissions. To enhance HEV performance in terms of fuel economy and emissions, and ensure user satisfaction with driving performance, the need for simultaneous optimization for the main parameters of powertrain components and control system is inevitable. However, this problem is challenging due to the large amount of coupling design parameters, conflicting design objectives and nonlinear constraints. Considering the defect of the methods which convert multi-objective optimization problems into single-objective ones, a comprehensive methodology based on the non-dominated sorting genetic algorithms II (NSGA II) to achieve parameter optimization for powertrain components and control system simultaneously and successfully find the Pareto-optimal solutions set is presented in this paper. A case simulation is carried out and simulated by ADVISOR, The simulation results show that this method can produce many Pareto-optimal solutions and a satisfactory solution can be selected by decision-makers according to their requirements. The results demonstrate the effectiveness of the algorithms proposed in this paper.

Micro embossing is an effective way to fabricate a polymethyl methacrylate (PMMA) specimen into micro-scale array structures with low cost and large volume production. A new method was proposed to fabricate a micro-lens array using a micro-electrical discharge machining (micro-EDM) mold. The micro-lens array with different shapes was established by controlling the processing parameters, including embossing temperature, embossing force, and holding time. In order to obtain the friction coefficient between the PMMA and the mold, ring compression tests were conducted on the Shenzhen University’s precision glass molding machine (SZU’s PGMM30). It was found that the friction coefficient between the PMMA specimen and the mold had an interesting change process with increasing of temperature, which affected the final shape and stress distribution of the compressed PMMA parts. The results of micro-optical imaging of micro-lens array indicated that the radius of curvature and local length could be controlled by adjusting the processing parameters. This method provides a basis for the fabrication and application of micro-lens arrays with low-cost, high efficiency, and mass production.

This study investigated the structural heterogeneity, mechanical property, electrochemical behavior, and passive film characteristics of Fe–Cr–Mo–W–C–B–Y metallic glasses (MGs), which were modified through annealing at different temperatures. Results showed that annealing MGs below the glass transition temperature enhanced corrosion resistance in HCl solution owing to a highly protective passive film formed, originating from the decreased free volume and the shrinkage of the first coordination shell, which was found by pair distribution function analysis. In contrast, the enlarged first coordination shell and nanoscale crystal-like clusters were identified for MGs annealed in the supercooled liquid region, which led to a destabilized passive film and thereby deteriorated corrosion resistance. This finding reveals the crucial role of structural heterogeneity in tuning the corrosion performance of MGs.

Inter-turn short circuit (ITSC) is a common fault in induction motors. However, it is challenging to detect the early stage of ITSC fault. To address this issue, this paper proposes an ITSC fault detection method for three-phase induction motors based on start-up current envelope energy. This approach uses Akima interpolation to calculate the envelope of the measured start-up current of the induction motor. A Gaussian window weighting is applied to eliminate endpoint effects caused by the initial phase angle, and the enveloping energy is obtained using the energy formula as the fault feature. Finally, by combining this with the support vector machine (SVM) classification learner, fault detection of ITSC in induction motors is achieved. The experimental results show that the average accuracy of this method reaches 96.9%, which can quickly and accurately detect ITSC faults in asynchronous motors and determine the severity of the faults. Furthermore, the average accuracy of SVM in detecting early ITSC faults under no-load conditions is 98.8%, which is higher than other classification learners, including LR, KNN, and NN. This study provides a new idea for induction motor fault detection and can contribute to induction motor maintenance.

This paper addresses the positioning tracking control problem for a second-order direct-drive linear switched reluctance machine (LSRM) motion control system based on the vectorization technique. In order to overcome the system matrix dimension oversize problem caused by vectorization method, the H-representation technique is adopted to reduce the closed-loop system matrix dimension. The stability conditions with lower computational complexity for the LSRM motion control system are obtained based on Lyapunov stability theory and the vectorization technique. The positioning tracking controller design method is proposed according to the matrix eigenvalue numerical analysis method. The proposed controller design method theoretically explicitly specifies the range of the designed controller gains, which can greatly reduce the burden of setting and tuning the control parameters as compared with proportion-integral-derivative (PID) parameters tuning method. Several groups of experimental tests are presented to verify the effectiveness of the proposed positioning tracking control method for LSRM motion control systems.