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One of the main obstacles to the robust optimization for permanent magnet machines is the high computational burden, which is mainly caused by the robustness evaluation process considering the manufacturing uncertainties. In this paper, a sequential sampling Kriging model is adopted to estimate the design robustness, and the problem of high-dimensional variables for the surrogate model due to uncertainties is avoided through adopting the worst-case based approach. To further reduce the number of finite element analyses (FEA) required for constructing a metamodel, a multi-points sequential sampling process with a two-step optimization oriented surrogate model updating algorithm is proposed. Compared with the FEA directly based robust optimization in previous work, similar Pareto Fronts are achieved by adopting the meta-model proposed algorithm but the overall run time reduced by 75%. In the end, an optimization problem for a 1.2 kW motor is considered by applying the proposed algorithm, and two prototypes with deliberately designed tolerances, imitating the worst-case scenarios in the real world, are manufactured. The worst-case torque ripple is reduced from 7.6% to 4.8% after optimizing, and this verifies the efficacy of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Permanent magnet synchronous machines (PMSMs) are widely used owing to high power density, high efficiency, etc. Core losses account for a significant component of the total loss in PMSMs beside winding losses. Therefore, it is necessary to consider core losses when designing PMSMs according to actual research applications. In this paper, taking four typical rotor structures (surface-mounted, embedded, "—" shape, "V" shape) as examples, an analysis method is proposed to predict the influence of different rotor structures on core loss of PMSMs. In the case of the same stator and winding structures, due to the influence of the rotor structure on the magnetic circuit, the corresponding variation law of the magnetic field in the stator core is studied. This method analyzes the radial and tangential components of magnetic flux density vector of the 4 representative points (stator tooth tip, middle tooth and yoke part), and then evaluates the entire core loss through finite element analysis results. In order to verify the method, a prototype was manufactured. The experimental results show good performance of the proposed method of this paper. It provides reference for selecting the appropriate rotor structure and designing the corresponding PMSM according to different specification. [ABSTRACT FROM AUTHOR]

In order to suppress the torque ripple of an open-end winding permanent-magnet synchronous machine (OEW-PMSM), a q-axis current injection method is typically employed but the disturbances caused by the third flux linkage parameter mismatch can augment the torque ripple. To solve this problem, in this paper, first, a zero-sequence current (ZSC) and zero-sequence back-EMF observer (ZCBO) are proposed based on an adaptive sliding mode control, which is able to simultaneously estimate ZSC and zero-sequence back EMF under varying conditions. Based on this ZCBO, the estimated ZSC and zero-sequence back EMF could compensate for the one-step control delay and suppress the aforementioned disturbances. Second, although central hexagon modulation is employed in the predictive current control (PCC) scheme, zero-sequence voltage (ZSV) still exists in the zero-sequence path due to the dead time of the inverter, affecting the predictive accuracy of the ZCBO. To accurately establish the ZCBO, the ZSV caused by the dead time of the inverter is considered in the ZCBO. Finally, a comparative study of two types of methods is presented, and simulations established by MATLAB software and experimental confirmations are carried out to verify the effectiveness of the proposed PCC scheme in this paper. [ABSTRACT FROM AUTHOR]

In an open-end winding permanent magnet synchronous machines drive with single dc voltage source, zero-sequence current (ZSC) can lead to a high current stress of power modules and loss of motor. Therefore, some modulation strategies have been employed to alleviate ZSC by suppressing zero-sequence voltage (ZSV). However, ZSC still exists in the system because ZSV can also be generated by other nonlinear factors of inverter such as the dead time of system. In addition, zero-sequence back electromotive force in the zero-sequence path can also enlarge torque ripple and ZSC. In order to deal with above problems, first, this paper proposes a full-order adaptive zero-sequence observer to estimate future ZSC and ZSV, which are able to compensate one-step control delay. Second, to achieve the maximum voltage dc bus utilization, this paper proposes a novel deadbeat predictive current control (DPCC) scheme with alternate sub-hexagonal center pulsewidth modulation strategy to suppress ZSC and torque ripple simultaneously. Finally, this paper presents a comparative study of two types of methods, namely traditional DPCC scheme and the proposed DPCC scheme. Simulation and experimental results are demonstrated to verify the effectiveness of the proposed DPCC scheme. [ABSTRACT FROM AUTHOR]

An electronic stability control (ESC) based on torque distribution is proposed for an eight in-wheel motor-independent drive electric vehicle (8WIDEV). The proposed ESC is extremely suitable for the independent driving vehicle to enhance its handling stability performance. The vehicle model is established based on a prototype 8WIDEV. A hierarchical control strategy, which includes a reference state generation controller, an upper-level vehicle controller, and a lower-level optimal control allocation controller, is utilized in the ESC. The reference state generation controller is used to obtain the ideal reference vehicle state. The upper-level vehicle controller is structured based on sliding mode control, which obtains the generalized objective force during 8WIDEV movement, therein considering the side slip angle and yaw rate. The lower-level optimal control allocation controller attempts to allocate the vehicle's objective force in each motor optimally and reasonably. The model is validated by field measurement results under the step input condition and snake input condition. Simulation results from a hardware-in-the-loop (HIL) simulation platform indicate that the ESC based on the optimized allocation proposed for 8WIDEV achieves better stability performance compared with direct yaw moment control (DYC). [ABSTRACT FROM AUTHOR]

Glomerular basement membrane (GBM) thickening is a typical and essential histopathological characteristic for the diagnosis of primary membranous nephropathy (PMN). The present study aimed to explore the relationship between GBM thickness and treatment response in PMN patients. A total of 128 patients with nephrotic syndrome concurrent with PMN were studied. The highest GBM thickness was measured from at least five glomerular capillary loops using an electron microscope, and the mean value was obtained. Patients were categorized into three groups according to the tertiles of GBM thickness as follows: Group 1 (GBM thickness ≤ 1100 nm, n = 48), Group 2 (1100 nm < GBM thickness ≤ 1300 nm, n = 40), Group 3 (GBM thickness >1300 nm, n = 40). Clinicopathological features and treatment response were compared among the three groups. The associations of GBM thickness with complete remission (CR) were assessed by Cox proportional hazard analyses and a cubic spline curve. During a median follow-up period of 25.80 months, 69 (53.9%) patients achieved CR. Kaplan–Meier analysis showed that the non-CR probability was significantly higher in the highest tertile of GBM thickness (p˂0.001). Univariate Cox proportional hazard analysis indicated that GBM thickness was associated with CR (HR per SD 0.617, 95% CI [0.471–0.809], p˂0.001). After adjusting for age, duration of PMN, estimated glomerular filtration rate (eGFR), urinary protein excretion, grade of C3 deposition, and titer of serum anti-phospholipase A2 receptor (PLA2R) antibody, GBM thickness remained an independent predictor of CR (HR per SD 0.580, 95% CI [0.436–0.772], p˂0.001). Further multivariable-adjusted restricted cubic spline analysis confirmed a significant reverse linear association between GBM thickness and CR (p for nonlinear = 0.1261). GBM thickness is an independent risk factor of CR. PMN patients with an increased level of GBM thickening at diagnosis have a lower probability of achieving CR. [ABSTRACT FROM AUTHOR]

The core loss is of great significance in the machine designing and optimization. In the paper, an analytical method for calculating the flux density of surface-mounted permanent magnet synchronous machine is first presented based on the equivalent magnetic circuit and conformal mapping method. The model takes into account the slotting effect and stator saturation. Subsequently, the core loss was calculated by improved Bertotti's formula in terms of the analytical model of flux density. Finally, experiment and finite element analysis (FEA) are used to validate the accuracy of the proposed analytical method for core loss. It shows that the analytical results for core loss can keep excellent agreement with the experimental results and FEA results. Therefore, the analytical model provides a great potential to the machine designing and optimization. [ABSTRACT FROM AUTHOR]

The efficiency performance of multi-motor-driven system highly depends on the power management. Three aspects of contribution have been made in this study. 1) A predictive power management for a DMPS is developed. To improve the performance of the predictive power management, an adaptive velocity predictor is proposed and the coefficients of proposed predictor can update its parameters according to identified driving patterns. Simulation results show that the new velocity predictor have best prediction performance compared with traditional predictors. 2) A neural network based power management is proposed. According to the optimization results of dynamic programming, radial-basis-function neural network is trained. The input dimensions and the number of hidden layer neurons of the neural network are optimized. 3) The performance of proposed control strategies are compared with three different drive cycles including MANHATTAN cycle, Japanese 1015 cycle, and UDDSHDV cycle. Simulation results indicate that compared with original control strategy, the predictive control strategy and neural network based control strategy show better efficiency performance. The neural network based strategy is verified by hardware-in-loop experiment and experiment results indicate that the control performance in real hardware shows similar property with simulation results. [ABSTRACT FROM AUTHOR]

This paper examines the problem of optimizing hybrid electric vehicle (HEV) power management for fuel economy. This paper begins by presenting a pseudospectral algorithm to solve this optimization problem. Compared with traditional dynamic programming (DP)-based optimal power management approaches, this algorithm has two key advantages: It is numerically more efficient, and it furnishes both the optimal state and costate trajectories. Building on the second advantage, this paper proposes a two-level strategy for optimal power management in vehicles commuting along fixed routes. The upper level of the proposed strategy is a costate adaptation algorithm employing pseudospectral optimization, whereas the lower level is an instantaneous optimization controller employing Pontryagin's minimum principle (PMP). This paper shows its pseudospectral optimization algorithm and two-level strategy using numerical simulation for a series hybrid school bus. Parameters of the bus powertrain model are obtained from experimental component tests performed at the National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology. Simulation results show that the pseudospectral method reaches a solution close to DP with higher computational efficiency. Furthermore, the proposed two-level strategy is capable of adapting vehicle power management based on road-grade predictions, i.e., an attractive feature compared with more traditional online hybrid power management approaches such as the use of proportional integral derivative (PID) control for adaptive equivalent fuel consumption minimization [PID equivalent consumption minimization strategy (PID-ECMS)]. [ABSTRACT FROM PUBLISHER]

This paper suggests a high power density on-board integrated charger with active ripple compensation circuit for electric vehicles. To obtain a high power density and high efficiency, silicon carbide devices are reported to meet the requirement of high-switching-frequency operation. An integrated bidirectional converter is proposed to function as AC/DC battery charger and to transfer energy between battery pack and motor drive of the traction system. In addition, the conventional H-bridge circuit suffers from ripple power pulsating at second-order line frequency, and a scheme of active ripple compensation circuit has been explored to solve this second-order ripple problem, in which a pair of power switches shared traction mode, a ripple energy storage capacitor, and an energy transfer inductor. Simulation results in MATLAB/Simulink validated the eligibility of the proposed topology. The integrated charger can work as a 70 kW motor drive circuit or a converter with an active ripple compensation circuit for 3 kW charging the battery. The impact of the proposed topology and control strategy on the integrated charger power losses, efficiency, power density, and thermal performance has also been analysed and simulated. [ABSTRACT FROM AUTHOR]

For revealing the low-temperature performance of lithium-ion battery, an experimental study on the charge-discharge characteristics of a 35A . h lithium manganate battery cell is conducted under low temperature, and the consistency of battery is analyzed by voltage range. The results indicate that at low temperature, the charge-discharge performances of battery drop substantially (under -l0°t , the battery can only be charged to 60. 23% of its rated capacity at 10A; and under -40°t , only 22% of rated capacity can be discharged) , the charging and discharging internal resistances significantly increase and the consistency of battery deteriorates. So it is strongly recommended to use heating devise in lithium-ion battery pack for assuring the normal operation of electric vehicles at low temperature. [ABSTRACT FROM AUTHOR]

The typical motor has poor heat dissipation conditions that are limited by the installation space and working environment, and the high operation temperature increase has been a bottleneck to improve the power density and torque density. The inner rotor motor is considered to be the research object, and an oil-cooling structure for end winding and stator core is proposed. The heat inside the motor is mainly carried away through the lubricating oil in the form of heat conduction and convection heat transfer. The 3d motor model was built using the ANSYS software. The temperature field of the motor was simulated to analyze the temperature distribution inside the motor under rated and peak working conditions. The low-speed high-torque test and one-hour temperature-rise test of the motor prototype were performed on a bench built in the laboratory. The comparison between the test results with water-cooled motor shows that the temperature-rise rate of oil-cooled motor with the same electromagnetic structure is slower than that of water-jacketed cooled motor, and the temperature difference between the front and back of the motor decreases by 18 °C in half an hour. The oil-cooled method has a good cooling effect on the stator core and works for longer time under rated conditions. [ABSTRACT FROM AUTHOR]

Torque ripple reduction has become an active research area for permanent magnet synchronous machine (PMSM) drives. This paper presents a novel torque ripple reduction method based on harmonic current control. In the proposed method, the optimal harmonic current solution based on the torque ripple model with minimum stator resistive loss is derived in the rotor reference frame (RRF). The optimal harmonic currents are injected by the proposed harmonic current controller (HCC), wherein the magnitude of harmonic currents are defined as controller variables. To estimate the harmonic currents, the proposed method also utilizes the least mean square (LMS) based adaptive filter (AF), wherein the coefficients are defined as feedback to the proposed HCC. The proposed methodology is demonstrated using both simulations and experiments and is verified to reduce torque ripples of PMSM drives over a wide range of speeds. [ABSTRACT FROM AUTHOR]

Deadbeat predictive current control (DPCC) can predict motor behavior based on SPMSM model. However, during the operation of motor system, motor parameters (such as stator inductance and flux linkage) vary frequently according to different working conditions, which may lead to controller parameter mismatch, causing current harmonic content to increase and efficiency to decrease. In order to solve these problems caused by parameter variation, first, this paper proposes a current prediction error model by considering uncertainties of model parameters. Second, stator inductance and flux linkage are decoupled based on current prediction error model, which can reduce the interaction between parameters. Finally, the Kalman Filter (KF) algorithm is presented to filter the decoupled parameters. It is shown that the stator inductance and flux linkage can be identified accurately and the complexity of computation can be simplified. The traditional DPCC method, Extended Kalman Filter (EKF) based DPCC method and the proposed DPCC method are comparatively analyzed in this paper. Simulation and experiment indicate that the proposed parameter decoupling identification method can effectively reduce current harmonic content, current fluctuation and current tracking errors caused by parameter mismatch. [ABSTRACT FROM AUTHOR]

The two‐voltage‐vector (2VV) model predictive torque control (MPTC) has been widely discussed and compared to the conventional single‐voltage‐vector (1VV) MPTC in permanent magnet synchronous motor drive applications, where it was shown to have quick response and low torque ripple. An improved 2VV‐MPTC is set forth based on extended control set. In the proposed approach, the reference voltage vector is calculated using the established torque and flux deadbeat control and optimal calculation of the duty cycles. Moreover, to further improve the torque performance, the proposed algorithm is extended to three‐voltage vector (3VV), which is shown to achieve even better performance. Experimental results demonstrate that the proposed 2VV and 3VV‐MPTC algorithms have better computation efficiency and can significantly reduce torque ripple compared to the previous methods. [ABSTRACT FROM AUTHOR]

To improve the performance of open-winding permanent magnet synchronous motors (OW-PMSMs) with a common dc bus, a novel control method that can simultaneously eliminate parameter mismatch in the d-axis, q-axis, and zero-sequence loop (ZSL) is proposed. First, the parameter mismatches are analyzed. Second, an extended state observer (ESO), which can predict the current in the next instant and the disturbance caused by parameter mismatch, is established. By combining the ESO and the deadbeat predictive current control (DPCC) in the d-axis and q-axis, replacing the sampled current in the DPCC with the predictive current in the ESO, and considering predictive disturbance as a voltage reference feedforward compensation, one-step delay and the disturbance caused by parameter mismatch are addressed. Then, in the ZSL, the predicted zero-sequence disturbance is considered as a compensation for the reference zero-sequence voltage (ZSV). The ZSV is obtained using the zero-voltage vector redistribution strategy in alternate subhexagonal center pulsewidth modulation strategy. The proposed method enhances the robustness of OW-PMSM, against parameter mismatch in the d-axis, q-axis, or ZSL. To verify the effectiveness of the proposed method, simulation and experimental results obtained using the traditional DPCC method and the ESO+DPCC method are presented herein. [ABSTRACT FROM AUTHOR]

Finite-set model predictive current control (FS-MPCC) has been employed for machine drives owing to the good dynamic performance. Sensitivity to parameter variation is one of the main barriers to its widespread application. To overcome this barrier, this article proposes an improved FS-MPCC for surfaced permanent magnet synchronous machines (SPMSMs). The contribution of this article is developing a novel current update mechanism, where the variation of resistance, rotor flux linkage, and inductance is considered, in which a modified coordinate system that contains a stationary and rotary axis frame is introduced. In this case, the predicted parameter can be obtained more accurately based on this mechanism, which can suppress the disturbances caused by model parameter mismatch. In addition, SPMSM parameter mismatch effect on FS-MPCC performance is analyzed in this article, which testifies that resistance mismatch influence on current prediction error can be neglected in practical system. The proposed FS-MPCC is validated and compared with different state-of-the-art methods. Improvement of the proposed control strategy is validated by means of experimental results on a 2-kW test rig. [ABSTRACT FROM AUTHOR]

Permanent-magnet (PM) motors have been widely used in industrial applications and automobiles. However, owing to the design tolerances, manufacturing uncertainties, and material inconsistency, deviations from the ideal motor inevitably occur with parasitic effects, such as additional cogging torque and vibration. One of the most significant obstacles for evaluating these uncertainties is the large computational burden caused by the countless uncertain combinations, which must be computed via the finite-element method (FEM). Herein, a worst-uncertain-combination-analyze (WUCA) method is proposed to significantly reduce the computational cost. A widely used analytical method is modified to identify the origin of additional cogging-torque harmonics caused by uncertainties. Different types of uncertainties for the surface-mounted PM machine and interior PM machine can be analyzed simultaneously. With the WUCA method, the worst-case combinations can be confirmed theoretically; thus, FEM calculations for only a few combinations of uncertainties are required, rather than thousands. Compared with the widely adopted design of experiments based uncertain combining methods, the worst-case cogging torque obtained from the WUCA is higher. FEM verification of different pole/slot configurations revealed that the WUCA method was a general and effective method for quickly estimating the worst-case cogging torque under manufacturing uncertainties. [ABSTRACT FROM AUTHOR]

Conventional finite-control set model predictive current control predicts the motor behavior for every switching state and selects the voltage vector that can minimize the cost functions as an optimum voltage vector. To get rid of the model parameter dependency, a finite-control set nonparametric predictive current control (NPCC) was proposed before, which can predict future current behavior using the measured data instead of initial model parameters. However, one of the main issues that are limiting the current and torque ripple performance is a stagnant current update mechanism. To overcome this issue, this article proposes a novel current update mechanism that based on two most recent current variations to reconstruct the permanent magnet synchronous machine model. The proposed nonparametric predictive current control based on the current update mechanism can effectively reduce the torque ripple and enhance current performance in contrast to NPCC. Experiment results are demonstrated to verify the effectiveness of the proposed method under different operating conditions. [ABSTRACT FROM AUTHOR]

Model predictive current control (MPCC) can predict future motor behavior according to a motor model. In practice, however, motor parameters will vary at run time, and the parameter mismatch disturbances caused by the variation in motor parameters will deteriorate the MPCC performance. To suppress the parameter mismatch disturbances effectively, this paper proposes a modified MPCC with a current variation update mechanism. In contrast with the traditional current prediction equation that contains crude model parameters, the modified current prediction equation contains only measured information, taking advantage of the proposed current variation update mechanism, which can update the modified prediction equation within each sampling period. A simulation established by MATLAB software indicates that the proposed method can effectively suppress the parameter mismatch disturbances. Experiments are carried out to verify the correctness of the proposed method. [ABSTRACT FROM AUTHOR]

The recent trend in the design of the high-power density power converter generally reduces the rate of the device cooling process. As a result, increased thermal coupling among devices exists. Based on measurements, a thermal coupling resistances network (TCRN) model is proposed in this article. Considering different spacings and current values at a fixed value of case temperature (${T} _{\text {c}}$), the relationships between the case-to-ambient thermal resistance (${R} _{\text {ca}}$) of individual power devices and their thermal coupling resistance (${R} _{\text {cp}}$) to the adjacent device are established. The close correspondence of ${T} _{\text {c}}$ from the calculation of the different spacing and experimental results obtained from a thermal coupling measurement platform confirms the established TCRN model and the relationships. Traditional thermal models do not consider the changes of ${R} _{\text {ca}}$ and also ignore the effect of thermal coupling among the adjacent devices. Compared with these models, the proposed thermal resistances modeling approach provides a better understanding of the thermal behavior of power devices. [ABSTRACT FROM AUTHOR]

An electric aircraft propulsion system utilizes a high efficiency motor to generate thrust for electric aircraft. However, it can be challenging to maintain high efficiency for the fixed pitch propeller, which is commonly used in electric aircraft, through all phases of the flight. This paper investigates the power demands of the electric aircraft during the climb and the cruise phases according to the flight profile, and presents a model to estimate the energy consumption per flight. Simulation results suggest that the efficiency in the climb and the cruise phases can affect the energy consumption of an electric aircraft. Efficiency during the climb phase can have a significant effect on the capacity of the electric aircraft propulsion system. Based on the aforementioned results, this paper proposes a novel approach to achieve high efficiency, in which the optimal efficiency points of the electric aircraft propulsion system in the climb and the cruise phases can be obtained by solving an optimization problem with minimizing the energy consumption per flight as the object function and under the constraints that the climb and cruise phases must be successful. For testing purposes, the proposed method is adopted to the design of the electric aircraft propulsion system on a specific two-seater electric aircraft. Experimental results obtained from real flights suggest that the proposed method can reduce the energy consumption of the electric aircraft by over 10%, while reducing the capacity demand for the electric aircraft propulsion system. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate the efficacy and safety of a low-dose Rituximab (RTX) regimen driven by peripheral blood B lymphocyte count in the treatment of adult patients with nephrotic syndrome (NS) complicated with acute kidney disease (AKI). We conducted a prospective single-arm study to evaluate the effect of B cells–driven RTX regimen. Patients with NS (MCD, FSGS, MN, IgAN) complicated with AKI fulfilling the inclusion criteria were eligible for this study. Patients were followed up at intervals of 2 months. Student's t -test and Chi-squared test were used to analyze normally distributed continuous variables and non-normally distributed continuous variables, respectively. From August 2018 to January 2022, 23 patients met the inclusion criteria and agreed to participate in the study. 3, 9, and 11 patients were AKI stage 1, 2, and 3, respectively. From baseline to the latest follow-up, 20 patients had complete and partial recovery of renal function. Accompanied by depletion of B cells, significant reduction of urinary protein excretion, serum total cholesterol, and the number of relapses were observed during the 12 months after the first RTX infusion as compared with during the 12 months before RTX injection. The number of patients who maintained steroids and immunosuppressive medications also remarkably decreased. This study indicates that the targets-driven treatment of low-dose RTX can achieve a high remission rate and alleviate the loss of kidney function in treating NS with AKI. The long-term efficacy, side effects, and therapeutic economics of RTX are reasonable. [ABSTRACT FROM AUTHOR]

A number of driving system topologies have been developed for electric vehicles, but the topology design and optimal sizing always challenge the performance of electric vehicles. This paper attempts to address three aspects. First, two novel topologies were derived from the original dual-motor-driven system, and the efficiency models of the system components were built, including motor efficiency, planet gear system efficiency and drag loss of the wet clutch. Second, a systematic optimal sizing framework was constructed. The feasible region of the design parameters was divided into a certain number of grid points, and each grid point represented different design results. Then, a dynamic programming algorithm was applied to each grid point to locate the optimal control strategy and obtain the best grid points under different power levels. After that, a bi-level optimization method was applied at these selected grid points to find the optimal design parameters. Last, the simulation results showed that, compared with the original design, the new topology with two clutches can reduce energy loss by 12.4%, and the optimal design results for the original topology can reduce energy loss by 3.36%. [ABSTRACT FROM AUTHOR]

To further improve the operating efficiency of a dual-motor-driven electric bus, a simple and robust power-management strategy was proposed. This study is comprised of three parts. (i) A systematic modeling approach for the efficiency of a dual-motor propulsion system (DMPS), which contains a wet clutch, transmission gears, bearings and two driving motors, has been proposed and verified experimentally. The correlation coefficient between the experimental data and the model simulation data is approximately 0.9, which indicates the validity and reliability of the DMPS model. (ii) Pontryagin’s Minimum Principle (PMP) was applied to optimize the control strategy under three different types of driving cycles. Based on the analysis of the PMP control strategy, a two-parameter-based mode switching control was proposed for determining the optimal working mode of the DMPS. Then, a broken line-based power split control was developed, and the turning point was determined according to the optimization results. (iii) By combining the mode switching control strategy and the power split control strategy, a new control strategy was formulated, and its robustness was verified through six driving cycles. The simulation results show that the new control strategy can significantly improve the DMPS efficiency performance in different types of driving cycles compared with the original control strategy. [ABSTRACT FROM AUTHOR]

To improve the suppression ability of uncertain disturbance of the sliding mode control driving system of the surface-mounted permanent magnet synchronous motor (SPMSM) and to reduce the chattering of the control output, a robust sliding mode control strategy with an improved power reaching law (IPRL) is proposed in this paper. Compared with the traditional fast power reaching law (FPRL), the IPRL incorporates the sum of the power terms of the system state variables into the conventional power terms, and uses hyperbolic tangent saturation function to replace the piecewise function, which can effectively suppress the sliding mode chattering and improve the convergence speed of the system state to the sliding mode surface. Furthermore, the robust sliding mode speed controller and sliding mode current controller of the SPMSM are designed separately with the IPRL, and detailed simulation verification is carried out to reveal the effectiveness of the IPRL. Simulation and experimental results show that compared with the FPRL, the proposed IPRL can reduce the inherent chattering phenomenon in sliding mode control, and the IPRL-based speed and current control strategy can effectively improve the dynamic performance and robustness of the system. [ABSTRACT FROM AUTHOR]

Conventionally, the small mean and variance of peak-to-peak cogging torque of permanent magnet (PM) machines considering manufacturing uncertainties can be achieved by a robust design or by reducing the uncertainties range. However, the consequent compromise of other design objectives or the increase in the manufacturing costs are frequently inevitable. In this paper, the combination sequence of the uncertainties is highlighted and implemented to achieve a stable performance even for a non-robust design without increasing the cost too much. A PM assembling approach is proposed to mitigate the influences of PM uncertainties on cogging torque by means of combining the uncertainties in a particular sequence, where the effects of uncertainties would counteract each other. Both the singular type of PM uncertainties and the combined ones are considered in the assembling approach. Furthermore, the proposed approach is verified by comparing the cogging torque performance with PM randomly assembled models, where several hundreds of models featuring different uncertainties are calculated through the finite element method. The proposed approach is discussed, particularly for the application of mass production and a small amount of prototypes. Two prototypes with different PM assembling sequences are fabricated and further verify the effectiveness of the proposed PM assembling approach. [ABSTRACT FROM AUTHOR]

Permanent magnet synchronous motor (PMSM) possesses the advantages of low power loss, high power density and high torque density and, hence, has achieved broad applications in both industrial drives and home appliances. With the increasing demands for high power density, the PMSM often operates at high speed and high frequency, leading to high power loss and temperature rise. Consequently, proper consideration of power loss, including the core loss, has attracted much attention for the modelling, designing, controlling and optimizing of PMSMs. However, the widely used equivalent circuit model, capable of providing good analysis results with fast calculation, often ignores the core loss, which may lead to unsatisfactory motor performance. This paper aims to investigate the development of equivalent circuit models, with predictable core loss for PMSMs, and proposes novel equivalent circuit models, which improve the core loss prediction accuracy in the load conditions. Some thoughts about the further improvement of the models are proposed and discussed. [ABSTRACT FROM AUTHOR]

To improve the torque accuracy for open-end winding permanent magnet synchronous motor (OEW-PMSM) with common dc bus, it is necessary to eliminate the zero-sequence torque (ZST) caused by zero-sequence current (ZSC) and the third back electromotive force. But the third flux linkage mismatch can enlarge ZSC which causes torque ripple. To deal with the above problem, firstly, a q-axis current injection method combined with deadbeat predictive current control (DPCC) is adopted to inject an extra current into the reference q-axis current. The extra torque generated by this injected current can compensate for ZST. Secondly, to ensure the accuracy of the q-axis injected current, a parameter identification method based on recursive least square (RLS) algorithm with forgetting factor is presented to identify the third flux linkage accurately. The identification value can reduce ZSC and torque ripple under different working conditions. And the accurate q-axis injected current can be obtained to counteract ZST and output accurate torque. Finally, three methods are comparatively analyzed in this paper, namely the traditional DPCC method, the DPCC method with q-axis current injection and the proposed DPCC method based on RLS with forgetting factor. The simulation and experimental results verify the effectiveness of the proposed DPCC method. [ABSTRACT FROM AUTHOR]

This article discusses a method to consider the effects of the manufacturing uncertainties on the additional cogging torque harmonics. With this method, the sensitivity analysis can be incorporated into the design stage instead of just checking it afterwards. With the authors’ previous work of the worst-uncertain-combination-analysis (WUCA) method, several design parameters and their effects on the additional cogging torque harmonics under uncertainties are discussed. It is demonstrated that a design with inherent robustness can be obtained through the proper selection of pole-arc coefficient and slot-opening width. In addition, a sensitivity index is proposed to estimate the effects of parameter uncertainties on torque harmonics. Some suggestions on improving the design robustness are consequently provided from the aspects of tolerances control and parameter design. The deductions are verified through finite element analysis (FEA) on different pole/slot configurations. [ABSTRACT FROM AUTHOR]

The current study aimed to assess the dietary salt intake in patients with CKD in Jiangsu province and investigate the relationship of urinary sodium excretion with blood pressure. A total of 800 patients with CKD stages 1–4 were recruited. All enrolled patients were asked to collect complete 24‐h urine specimen. At the same time, patient's demographic and laboratory data were recorded. The mean age was 47.45 ± 15.25 years old, including 423 men and 377 women. There was no significant difference in urinary sodium excretion among different stages of CKD (p =.748). This study revealed that the median urinary sodium excretion of all patients was 127.20 mmol/d (IQR 91.03–172.06), corresponding to a salt intake of 7.4 g/d. Among them, only 167 (20.9%) cases had salt intake <5 g/d. Moreover, urinary sodium excretion in overweight group and obese group was higher than that in normal weight group (p =.001, p ˂.001). Likewise, urinary sodium excretion in men was higher than that in women (p ˂.001). Spearman correlation analysis indicated that urinary sodium excretion positively correlated with urinary protein excretion (r =.178, p ˂.001), SBP (r =.109, p =.002), and DBP (r =.086, p =.015). After adjusting for age, gender, BMI, eGFR, urinary protein excretion, and history of taking antihypertensive drug, multivariate linear regression demonstrated that higher level of urinary sodium excretion associated with increased level of SBP, DBP, and MAP (β = 0.020, p =.049; β = 0.015, p =.040; β = 0.016, p =.025, respectively). In conclusion, the dietary salt intake in CKD patients, especially in male, overweight and obese subjects, remains high in Jiangsu province. It is vital to decline salt intake to control blood pressure in Jiangsu patients with CKD. [ABSTRACT FROM AUTHOR]

• Inflammation has emerged as a hallmark in the pathogenesis of diabetic kidney disease. • PLR reflects platelet activation and the systemic inflammatory status. • PLR was significantly associated with proteinuria and prognosis in DKD patients. • PLR was an independent prognosticator for renal progression in biopsy-proven DKD. • PLR might serve as a useful and convenient biomarker to predict DKD progression. Growing evidence points to the pivotal role of inflammation in the pathogenesis of diabetic kidney disease (DKD). However, as an inflammation-based prognostic score, the significance of platelet-to-lymphocyte ratio (PLR) in biopsy-proven DKD remains uncertain. Therefore, the current study aimed to evaluate the association of PLR with the clinicopathological features and the progression of DKD. In total, 167 patients with biopsy-proven T2DKD were retrospectively recruited. Clinicopathological characteristics were compared according to the tertiles of baseline PLR. Pearson's or Spearman correlations were used to examine the associations between PLR and baseline characteristics. Assessment of the prospective relationship of PLR with the kidney outcomes defined as a doubling of baseline serum creatinine or onset of end stage renal disease (ESRD), were investigated by Kaplan-Meier survival analysis. Moreover, a cubic spline curve was further calculated to explore the significance of PLR in DKD prognosis. On top of that, identification of the risk factors associated with DKD progression was executed by a model of Cox proportional hazards. Median follow-up period was 23.77 months, during which 92 (55.1%) patients confronted DKD progression. Pearson's correlation indicated that urinary protein increased along with PLR rising (r = 0.193, P = 0.012). Kaplan–Meier survival curves revealed a significantly increased probability of event-free survival in the lowest tertile of PLR compared to those in the highest tertile (P = 0.018). A statistical linear correlation between PLR and DKD development was demonstrated by a restricted cubic spline analysis (P for nonlinear = 0.784). In addition, the analyses of multivariate Cox regression indicated that elevated PLR had an association with a greater risk of DKD progression (HR 1.004, 95%CI [1.000–1.008], P = 0.035), which was verified to be an independent risk factor for renal outcomes. Our findings demonstrated that the PLR was associated with proteinuria and prognosis in DKD patients. It was an independent risk factor for kidney progression in biopsy-proven DKD. [ABSTRACT FROM AUTHOR]

One of the main obstacles to applying the robust optimization for the permanent magnet motors is the high computational burden, which is mainly caused by the robustness evaluation considering the manufacturing uncertainties. In this article, efforts are made to speed up the process of robust optimization, from the aspects of reducing the computational cost, and avoiding the computing resources being wasted. Firstly, several widely used methods, aiming to identify the worst-case performance under uncertainties, are examined, and compared. And the efficient worst-uncertain-combination-analysis (WUCA) method is consequently adopted to significantly reduce the computational cost of robustness evaluation. From another aspect, the parameter rounding (PR) operation is inevitable due to the constraint of manufacturing accuracy, but its adverse effects on the optimization are often ignored. It is found that parts of the computing resources might be wasted during the optimization. A new PR during the calculation (PRDC) method is proposed, and incorporated into the process of robust optimization. Compared with the conventional one, similar results can be achieved with the computational time reduced by approximately $\text{11}\%$ in the PRDC modified robust optimization. [ABSTRACT FROM AUTHOR]

Objective: Although diabetic kidney disease (DKD) has been considered as a glomerulocentric disease in the past few decades, growing evidence demonstrated that tubular damage was indispensable in its pathogenesis and progression. This study was designed to investigate the association of urinary acidification dysfunction with the progression of DKD in type 2 diabetic patients.Methods: Here the urinary acidification functions were measured from 80 participants with renal biopsy-proven DKD. The different kinds of renal tubular transportation dysfunction were analyzed, including the dysfunction of bicarbonate reabsorption, titratable acid secretion, and ammonium secretion. In addition, patients were followed up for 17 (interquartile range, 11-32) months to evaluate the effect of urinary acidification dysfunction in the progression of DKD.Results: The most common urinary acidification dysfunction was the disorder of ammonium secretion, accounting for 53.75%. The more proteinuria excretion and the lower glomerular filtration rate (GFR) were observed in the urinary titratable acid disorder group than the normal group, and the same results were obtained for ammonium secretion disorder. Urine titratable acid was positively correlated with eGFR whereas it was inversely correlated with proteinuria, serum creatinine, and BUN. Moreover, 24 h urine protein, serum creatinine, BUN and cystatin C increased from DKD stage II to stage IV, whereas the eGFR and urine titratable acid decreased in the same way. Furthermore, Kaplan-Meier analysis and Cox regression showed that the disorder of titratable acid was an independent risk factor for DKD progression.Conclusions: The dysfunction of urinary titratable acid is a potential biomarker for the severity of proteinuria, eGFR and glomerular lesions in patients with DKD. Moreover, the titratable acid disorder is an independent risk factor of the DKD progression. [ABSTRACT FROM AUTHOR]

We compared the prognostic value of nutritional or volumetric parameters measured by body composition in hospitalized patients on maintenance hemodialysis. We conducted a cohort study to assess the association of different parameters of body composition with all-cause mortality in inpatients admitted to our nephrology department from January 2014 to December 2016. Of the 704 study patients, 160 (22.7%) died during a median follow-up of 33 months. In multivariate adjusted Cox models, higher ratio of extracellular water to body cell mass (ECW/BCM) (adjusted HR per 1-SD, 1.49; 95% CI, 1.19 to 1.85), lower lean tissue index (LTI) (adjusted HR per 1-SD, 0.70; 95% CI, 0.57 to 0.86) and lower body cell mass index (BCMI) (adjusted HR per 1-SD, 0.70; 95% CI, 0.58 to 0.85) were associated with a significantly greater risk of death. When these parameters were added to the fully adjusted model, BCMI performed best in improving the predictability for all-cause mortality (integrated discrimination improvement = 0.02, P = 0.04; net reclassification index = 0.11, P = 0.04). Among body composition indexes, ECW/BCM was the most relevant fluid volume indices to mortality and BCMI and LTI were the most relevant nutritional status indices to mortality in maintenance hemodialysis patients. [ABSTRACT FROM AUTHOR]

Abstract Aims Acute kidney injury (AKI) can limit the clinical use of cisplatin in cancer treatment. The drivers of cisplatin-induced AKI include oxidative stress, mitochondrial dysfunction and apoptosis. Previous studies showed renalase protected cultured human renal proximal tubular cell (HK-2) against cisplatin induced necrosis, and renalase-knockout mice subjected to cisplatin showed exacerbated kidney injury. Therefore, it is necessary to determine the exact mechanisms of renalase in cisplatin-induced nephrotoxicity. Main methods To study the protective effect of renalase on cell viability, renal function, apoptosis, reactive oxygen species (ROS) production and mitochondrial dynamics, cultured HK-2 cells and male mice were subjected to cisplatin. Signaling proteins related to apoptosis, survival, and mitochondrial fission were analyzed by Western blot. Key findings In this study, we showed that the protective effect of recombinant renalase in cisplatin-induced AKI was associated with the regulation of ROS production, mitochondrial dynamics and sirtuin-3 (Sirt3) levels in vivo and in vitro. After cisplatin treatment, recombinant renalase restored Sirt3 expression, reduced mitochondrial fission and ROS generation. In HK-2 cells, downregulation of endogenous Sirt3 expression by siRNA transfection abrogated the renalase cytoprotection. Significance Our study suggests that renalase protects against cisplatin-induced AKI by improving mitochondrial function and inhibiting oxidative stress, and in vitro , it functions in a Sirt3-dependent manner. [ABSTRACT FROM AUTHOR]

Soft magnetic composite (SMC) materials and SMC electromagnetic devices have attracted strong research interest in the past decades. However, SMC devices have large core loss that needs to be put into consideration even at the design stage. Effective and accurate prediction of the core loss becomes crucial for the design and optimization of high-performance motors with these materials. Equivalent circuit model is a widely used method for machine analysis, due to the advantages in the fast calculation with a clear physical mechanism. This paper presents an equivalent circuit model to predict the core loss of a claw-pole permanent magnet motor with SMC stator core. All the parameters including the equivalent core-loss resistance in the equivalent circuit model are identified based on the finite-element method to achieve high accuracy, and the effectiveness of the parameters identification methods is experimentally verified. The proposed equivalent circuit model can predict the core loss and motor’s performance efficiently both under no-load and loading conditions. [ABSTRACT FROM AUTHOR]

Cisplatin often causes acute kidney injury (AKI) in the treatment of a wide variety of malignancies. Mitochondrial dysfunction is one of the main reasons for cisplatin nephrotoxicity. Previous study showed that Pink1 and Parkin play central roles in regulating the mitophagy, which is a key protective mechanism by specifically eliminating dysfunctional or damaged mitochondria. However, the mechanisms that modulate mitophagy in cisplatin induced nephrotoxicity remain to be elucidated. The purpose of this study was to investigate the effects of Pink1/Parkin pathway in mitophagy, mitochondrial dysfunction and renal proximal tubular cells injury during cisplatin treatment. In cultured human renal proximal tubular cells, we found that knockdown of Pink1/Parkin induced the aggravation of mitochondrial function, leading to the increase of cell injury through inhibition of mitophagy. Additionally, the overexpression of Pink1/Parkin protected against cisplatin-induced mitochondrial dysfunction and cell injury by promoting mitophagy. Our results provide clear evidence that Pink1/Parkin-dependent mitophagy has identified potential targets for the treatment of cisplatin-induced AKI. [ABSTRACT FROM AUTHOR]

Aims: RNA-binding protein Human antigen R (HuR) is closely related to diabetic nephropathy (DN) pathogenesis. However, the capacity of histological HuR level as a biomarker for DN progression remains unclear.Methods: A total of 147 patients with type 2 diabetes mellitus who had biopsy-proven DN were enrolled. Renal outcomes were defined by doubling serum creatinine level or progression to end-stage renal disease (ESRD). A nomogram was built to predict renal outcomes based on Cox proportional hazards regression.Results: The median follow-up period was 31 months, during which 71 (48.30 %) patients confronted DN progression. Pearson's correlation indicated that histological HuR increased along with DN pathological class rising (r = 0.776, p < 0.001). Notably, multivariate Cox regression analysis showed that elevated HuR was associated with a greater risk of DN progression (HR 2.431, 95 %CI: 1.275-4.634, p = 0.007) beyond 6 months after renal biopsy. Patients in the higher HuR expression group had lower cumulative renal survival rates beyond the first 6 months. Simultaneously, a well-performed nomogram including HuR classification, was developed to predict the individual progression risk (C-index 0.828).Conclusions: Our findings demonstrated that the histologic HuR expression was an independent risk factor for kidney progression beyond 6 months after renal biopsy in DN. [ABSTRACT FROM AUTHOR]

This paper presents a computationally efficient loss prediction procedure and thermal analysis of surface-mounted brushless AC permanent magnet (PM) machine considering the UDDS driving duty cycle by using a lumped parameters’ thermal model. The accurate prediction of loss and its variation with load are essential for thermal analysis. Employing finite element analysis (FEA) to determine loss at every load point would be computationally intensive. Here, the finite element analysis and/or experiment based computationally efficient winding copper and iron loss and permanent magnet (PM) power loss models are employed to calculate the electromagnetic loss at every operation point, respectively. Then, the lumped parameter thermal method is used to analyse the thermal behaviour of the driving PM machine. Experiments have been carried out to measure the temperature distribution in a motor prototype. The calculation and experiment results are compared and discussed. [ABSTRACT FROM AUTHOR]

This paper describes a computationally efficient approach for mapping rotor power loss in permanent magnet (PM) machines. The PM loss mapping methodology discussed here utilizes a small number of time-step finite-element analyses (FEAs) to determine the parameters of a functional representation of loss variation with speed (frequency) and stator current and is intended for a rapid evaluation of machine performance over the entire torque–speed envelope. The research focus is placed on field-oriented-controlled brushless AC PM machines with surface-mounted PM rotor construction, although the method could be adapted for other rotor formats. The loss mapping procedure accounts for the axial segmentation of the PM array through the use of an equivalent electrical resistivity of the segmented PM array, which is obtained from three-dimensional (3-D) FEA. The PM loss can be accurately mapped across the full operational envelope, including the field-weakened mode, through a single 3-D and four two-dimensional time-step FEAs. The proposed methodology is validated on an 18-slot 16-pole surface-mounted brushless AC PM machine design. The loss mapping procedure results closely agree with the computationally demanding alternative of direct 3-D finite-element prediction of the PM power loss undertaken at each of the machine's operating points. [ABSTRACT FROM PUBLISHER]

Objectives: Diabetes is associated with a high incidence of microvascular disease, including nephropathy. The current study aimed to investigate the association of urinary calcium and phosphorus excretion with chronic kidney disease (CKD) progression in type 2 diabetes mellitus.Methods: A total of 159 T2DM patients with chronic kidney disease (CKD stage G1-G4) were retrospectively included. Patients were categorized into three groups according to the tertiles of 24-h urinary calcium and phosphorus excretion, respectively. Clinical parameters and laboratory findings were compared among the three groups. Cox proportional hazards models were used to estimate the associations of urinary calcium and phosphorus excretion with CKD progression and adjusted for baseline eGFR, urinary protein excretion, mean arterial pressure, and use of RAAS inhibitor. A cubic spline curve was used to explore the association between urinary calcium excretion and CKD progression, as well as urinary phosphorus excretion and CKD progression. Moreover, the subgroup effects of urinary calcium and phosphorus excretion on CKD progression were estimated using Cox regression. CKD progression was defined as double of baseline serum creatinine or occurrence of ESRD.Results: During a median of 18.23 months of follow-up, the composite renal outcomes were noted in 27%. Cumulative renal outcomes were significantly lower in the highest tertile of urinary calcium excretion and phosphorus excretion in Kaplan-Meier analyses. The multivariate Cox proportional hazards regression analyses indicated that both the highest tertile of urinary calcium and phosphorus excretion was associated with a lower risk for CKD progression compared with the lowest tertile. Restricted cubic spline analyses of the association between urinary calcium excretion and CKD progression indicated a linear association. Additionally, there was also a linear association between urinary phosphorus excretion and CKD progression. Subgroup analyses showed that higher urinary phosphorus excretion was particularly associated with a lower risk of CKD progression in non-diabetic kidney disease (NDKD) patients.Conclusion: Higher urinary calcium and phosphorus excretion were associated with decreased risk of CKD progression in T2DM patients. [ABSTRACT FROM AUTHOR]

Objective: Chronic kidney disease (CKD) related to diabetes has become more common than glomerulonephritis in recent years. Given the inefficient and difficult identification of diabetic kidney disease (DKD) from non-diabetic kidney disease (NDKD) as well as a result of emerging evidence supporting a role for tubular involvement in DKD, we aimed to investigate the utility of urinary neutrophil gelatinase-associated lipocalin (uNGAL) in the differential diagnosis and predictive value of DKD from NDKD.Methods: Data for 100 type 2 diabetic patients with CKD at our center from June 2016 to August 2019 were reviewed. All the patients were categorized into 2 groups by the renal biopsy results: DKD and NDKD. Urinary NGAL levels were normalized by urinary creatinine and calculated as uNGAL/creatinine ratios (uNCR). The independent factors of the occurrence of DKD and the diagnostic implications of uNCR were explored by logistic regression and receiver-operating characteristic (ROC) curve analysis. In addition, we analyzed the relationship between uNCR and proteinuria in patients with DKD by Pearson test and linear regression. Kaplan-Meier survival analysis was performed to assess the prospective association of uNCR with the renal outcome.Results: Significantly higher levels of uNCR were observed in patients with DKD when compared to those with NDKD (28.65 ng/mg vs 27.47 ng/mg, p< .001). uNCR was identified as an independent risk factor for the occurrence of DKD in diabetic patients with CKD (odds ratio [OR] = 1.020; 95%CI = [1.001-1.399], p = .042). The optimal cutoff value of uNCR for predicting DKD was 60.685 ng/mg with high specificity (90.5%) but relatively low sensitivity (55.7%). In Pearson test, uNCR was positively correlated with proteinuria, serum creatine, blood urea nitrogen, duration of diabetes, interstitial inflammation score and global sclerosis, whereas it was inversely correlated with eGFR, hemoglobin, serum albumin and 25-hydroxy vitamin D. Furthermore, in a fully adjusted model including eGFR, serum albumin and total cholesterol, the group with uNCR>60.685 ng/mg was associated with 7.595 times higher likelihood of nephrotic-range proteinuria compared to the group with uNCR≤60.685 ng/mg. In the Kaplan-Meier survival analysis, the event-free survival probability in patients with uNCR>60.685 ng/mg was significantly lower than those with uNCR≤60.685 ng/mg (p = .048).Conclusions: uNCR might serve as a potential tool for identifying cases in which there was a high clinical suspicion of DKD and that in whom confirmatory biopsy could be considered, and the best predictive cutoff value of normalized uNCR for DKD diagnosis was 60.685 ng/mg. Type 2 diabetic patients with increased level of uNCR had higher risk to nephrotic-range proteinuria and worse renal outcome. [ABSTRACT FROM AUTHOR]