An improved two-vector model predictive torque control based on RMS duty ratio optimization for pmsm

This paper proposes an improved two-vector model-predictive torque control (MPTC) strategy to reduce the average torque ripple and improve the flux tracking performance. When determining the duty ratio of vector combination, this method aims at restricting the root mean square (RMS) error of both torque and flux during the whole control period. Every vector combination and corresponding time duration are evaluated in the cost function, which leads to global restriction of torque ripple and flux ripple. In order to avoid increasing switching frequency and computational burden, a restriction is added on the second vector. The three candidates of the second vector are the two adjacent vectors of the first one and zero vector. Simulation results are provided to show the effectiveness of the proposed strategy

Current boundary based model predictive torque control of PMSM

In this paper, a current boundary based model predictive torque control is proposed to improve torque and flux control performance of permanent magnet synchronous motor (PMSM). To reduce torque and flux ripple, two voltage vectors are applied in one control period. Based on the current variations under the two vectors, torque is forced to reach a preset boundary at the end of a control period and can be limited to a band during the whole period. In addition, according to the predictive switching instants and the predictive current, some vector combinations can be excluded from the control set, which significantly reduces the computational burden of cost function evaluation. Simulation results reveal the effectiveness of the proposed strategy

Reference voltage vector based model predictive torque control with RMS solution for PMSM

To reduce the computational burden of a conventional model predictive torque controller (MPTC), a reference voltage vector based MPTC strategy is proposed. The reference voltage vector is obtained from the reference stator flux vector and the reference torque. According to the location of the reference voltage vector, a first optimal vector can be determined in a quite straightforward way, improving the system dynamic performance. Furthermore, in order to decrease the torque and flux ripple, a root mean square (RMS) based solution is employed to generate the reference voltage vector and calculate the duty ratio. This method aims at minimizing the RMS error of flux and torque during the whole control period. Then, the steady state performance is improved. Besides, since the new cost function contains only the reference voltage vector, the weighting factor in conventional MPTC is eliminated. In addition, to keep a balance between the steady state performance and switching frequency, the candidates for the second optimal vector are restricted to a certain scope. Simulations were carried out and the results verified the validation of the proposed MPTC strategy

Identification of Pharmacokinetic Markers for Guanxin Danshen Drop Pills in Rats by Combination of Pharmacokinetics, Systems Pharmacology, and Pharmacodynamic Assays

This paper reported a feasibility study strategy of identifying pharmacokinetic (PK) markers for a cardiovascular herbal medicine, Guanxin Danshen drop pill (GDDP). First, quantification analysis revealed the constituent composition in the preparation by high-performance liquid chromatography (HPLC). Subsequently, physiochemical property calculation predicted the solubility and intestinal permeability of the constituents in the preparation. Furthermore, HPLC–MS analysis ascertained the absorbable ingredients and their PK properties in rat plasma. The main effective substances from the ingredients absorbed into blood and their cardiovascular effects were also predicted by systems pharmacology study, and were further confirmed by in vivo protective effects on isoprenaline-induced myocardial injury in mice. Finally, the ingredients with high content, representative structure feature, favorable PK properties, high relevant degree to myocardial ischemia (MI) issues, and validated therapeutic effects were considered as the PK markers for the preparation. Ginsenosides Rg1, Rb1, and tanshinone (TS) IIA were identified originally as PK markers for representing PK properties of GDDP. In addition, integrated PK studies were carried out according to previous reports, viz. drug concentration sum method and the AUC weighting method, to understand the in vivo process of GDDP comprehensively. The present study maybe provide a reference approach to identify PK markers for cardiovascular herbal medicines

Indigo: a natural molecular passivator for efficient perovskite solar cells

Organic–inorganic hybrid lead halide perovskite solar cells have made unprecedented progress in improving photovoltaic efficiency during the past decade, while still facing critical stability challenges. Herein, the natural organic dye Indigo is explored for the first time to be an efficient molecular passivator that assists in the preparation of high-quality hybrid perovskite film with reduced defects and enhanced stability. The Indigo molecule with both carbonyl and amino groups can provide bifunctional chemical passivation for defects. In-depth theoretical and experimental studies show that the Indigo molecules firmly binds to the perovskite surfaces, enhancing the crystallization of perovskite films with improved morphology. Consequently, the Indigo-passivated perovskite film exhibits increased grain size with better uniformity, reduced grain boundaries, lowered defect density, and retarded ion migration, boosting the device efficiency up to 23.22%, and ˜21% for large-area device (1 cm2). Furthermore, the Indigo passivation can enhance device stability in terms of both humidity and thermal stress. These results provide not only new insights into the multipassivation role of natural organic dyes but also a simple and low-cost strategy to prepare high-quality hybrid perovskite films for optoelectronic applications based on Indigo derivatives.Peer ReviewedPostprint (author's final draft

Nonlinear Reduced-Order Observer-Based Predictive Control for Diving of an Autonomous Underwater Vehicle

The attitude control and depth tracking issue of autonomous underwater vehicle (AUV) are addressed in this paper. By introducing a nonsingular coordinate transformation, a novel nonlinear reduced-order observer (NROO) is presented to achieve an accurate estimation of AUV’s state variables. A discrete-time model predictive control with nonlinear model online linearization (MPC-NMOL) is applied to enhance the attitude control and depth tracking performance of AUV considering the wave disturbance near surface. In AUV longitudinal control simulation, the comparisons have been presented between NROO and full-order observer (FOO) and also between MPC-NMOL and traditional NMPC. Simulation results show the effectiveness of the proposed method

Full Operating Range Optimization Design Method of LLC Resonant Converter in Marine DC Power Supply System

The marine DC power supply system is the key to a ship’s power supply, which needs to convert the energy from storage batteries or distributed power generation units into stable DC voltage for electric propulsion or the ship’s electronics. The LLC resonant converter can be used as the key power conversion link in the marine DC power supply system due to its ability to realize electrical isolation in a high-power environment and soft switching within a wide load range. Aiming at the problem of sudden changes in voltage gain at a high switching frequency under light load conditions and the problem of insufficient voltage gain under heavy load conditions due to the parasitic parameters of power devices (mainly referring to the junction capacitor), this paper first proposes a full operating range performance optimization design method. By adding an auxiliary circuit that can be opened according to the operating conditions and a multi-objective particle swarm parameter optimization method that considers the converter loss and voltage gain under heavy load conditions, the performance of the LLC resonant converter can be improved in a full range of operating conditions. Finally, the effectiveness of the proposed method is verified by an experimental prototype and compared with the conventional methods and existing solutions to highlight the superiority of the proposed method in this paper

Impact of Skin Effect, Resistive and Dielectric Losses on Current Estimation and Reliability of ULSI Interconnects

Abstract: In this study, a series connection system of interconnects and gates is studied. In the system, we focus on skin effect, resistive and dielectric losses in previous level interconnects and the impact of their variations on the fast current estimation and the lifetime calculation of the post level interconnects. The changes in cross-section dimensions of interconnects are used to represent their differences in resistances, dielectric losses and skin effect in actual circuits or to represent the process of Electro Migration (EM). Through the analysis of the voltage transfer function of interconnects, the different roles of skin effect, resistive and dielectric losses in signal attenuation for interconnects of various cross-sections are pointed out. The study shows that the input voltage waveforms of the post level interconnects will change if the cross-section sizes of the previous level interconnects vary. By means of showing the changing tendencies of current and lifetime estimation results affected by the cross-section dimensions of the previous interconnects, we indicate that the fast current and reliability estimation results will not be accurate enough if these effects are not included

Bilevel Optimization-Based Time-Optimal Path Planning for AUVs

Using the bilevel optimization (BIO) scheme, this paper presents a time-optimal path planner for autonomous underwater vehicles (AUVs) operating in grid-based environments with ocean currents. In this scheme, the upper optimization problem is defined as finding a free-collision channel from a starting point to a destination, which consists of connected grids, and the lower optimization problem is defined as finding an energy-optimal path in the channel generated by the upper level algorithm. The proposed scheme is integrated with ant colony algorithm as the upper level and quantum-behaved particle swarm optimization as the lower level and tested to find an energy-optimal path for AUV navigating through an ocean environment in the presence of obstacles. This arrangement prevents discrete state transitions that constrain a vehicle’s motion to a small set of headings and improves efficiency by the usage of evolutionary algorithms. Simulation results show that the proposed BIO scheme has higher computation efficiency with a slightly lower fitness value than sliding wavefront expansion scheme, which is a grid-based path planner with continuous motion directions