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In this paper, a novel magnetic parameter design methodology is proposed for switched reluctance motors (SRMs). Based on the nonlinear characteristic of flux linkage, the design equations of structural and winding parameters are derived. The benefit is that there are no meaningless empirical design coefficients in the proposed design methodology. Three SRMs with multiple phases, i.e., 12/8, 10/8, and 18/20 stator/rotor poles SRMs, are initially designed according to the derived equations. Then, multiobjective optimization is carried out to realize the design objectives of output torque, current density, and torque ripple. The design solutions of the three SRMs with similar current density and slot fill factor are selected from the Pareto front, respectively, and the performance comparisons are conducted. The proposed design methodology is verified by the selected optimal solutions after the substitution into the design equations. Finally, the designed SRMs are prototyped and tested to validate the simulation results and further verify the effectiveness of the proposed design methodology. [ABSTRACT FROM AUTHOR]

—The plug-in hybrid electric bus (PHEB) is one of the vehicles that can address global environmental and energy problems. Due to the complex characteristics of the urban cycle condition, a fixed parameter energy management strategy may not be suitable for fuel economy. Thus, an adaptive real-time control strategy seems to be of great significance for PHEBs. The paper designs an advanced equivalent consumption minimization strategy (ECMS) with segments divided from the driving cycle and optimized equivalent factor (EF). The classification of different segments is based on the time that the vehicle stops. The EF is optimized under two different driving conditions by using the grey wolf optimization (GWO) algorithm. A new model, as the difference between the actual state of charge (SOC) and the reference SOC, is presented and minimized by optimizing the EF. Segmented EF optimization adds a correction factor, which can adjust EF according to the kinematic characteristics of each segment. The results show that the fuel consumption decreased by 18.72 % compared with the conventional ECMS. • An advanced equivalent consumption minimization strategy with segmented equivalent factor (EF) optimization is proposed. • The rational reference state of charge (SOC) trajectory is established using current operating conditions. • The EF is optimized by the grey wolf optimization (GWO) algorithm as to track the reference SOC. • A correction coefficient is created to maximize the superior EF for various road segments within the same cycle. [ABSTRACT FROM AUTHOR]

Along with the developing of flexible electronics, there is a strong interest in high performance flexible energy storage materials. As natural carbohydrate polymer, cellulose fibers have potential applications in the area due to their biodegradability and flexibility. However, their conductive and electrochemical properties are impossible to meet the demands of practical applications. In this study, cellulose fibers were combined with polyaniline to develop novel paper-based supercapacitor electrode material. Cellulose fibers were firstly coordinated to Cu(II) and subsequently involved in polymerization of polyaniline. Not only the mass loading of polyaniline was significantly increased, but also an impressive area specific capacitance (2767 mF/cm2 at 1 mA/cm2) was achieved. The developed strategy is efficient, environmentally friendly, and has implications for the development of cellulosic paper-based advanced functional materials. [Display omitted] [ABSTRACT FROM AUTHOR]