Improved Model Predictive Current Control for SPMSM Drives With Parameter Mismatch

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

An Improved Model Free Predictive Current Control for PMSM with Current Prediction Error Variations

Funding Agency: Key Areas of Guangdong Province through the Project “Integration and Industrialization of High Performance, Long Endurance, and Integrated Electric Drive System” (Grant Number: 2019B090910001)Peer reviewedPublisher PD

Optimal Control Strategy Design Based on Dynamic Programming for a Dual-Motor Coupling-Propulsion System

A dual-motor coupling-propulsion electric bus (DMCPEB) is modeled, and its optimal control strategy is studied in this paper. The necessary dynamic features of energy loss for subsystems is modeled. Dynamic programming (DP) technique is applied to find the optimal control strategy including upshift threshold, downshift threshold, and power split ratio between the main motor and auxiliary motor. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement in reducing energy loss due to the dual-motor coupling-propulsion system (DMCPS) running is realized without increasing the frequency of the mode switch

Current Challenges and Future Perspectives of Renal Tubular Dysfunction in Diabetic Kidney Disease

Over decades, substantial progress has been achieved in understanding the pathogenesis of proteinuria in diabetic kidney disease (DKD), biomarkers for DKD screening, diagnosis, and prognosis, as well as novel hypoglycemia agents in clinical trials, thereby rendering more attention focused on the role of renal tubules in DKD. Previous studies have demonstrated that morphological and functional changes in renal tubules are highly involved in the occurrence and development of DKD. Novel tubular biomarkers have shown some clinical importance. However, there are many challenges to transition into personalized diagnosis and guidance for individual therapy in clinical practice. Large-scale clinical trials suggested the clinical relevance of increased proximal reabsorption and hyperfiltration by sodium-glucose cotransporter-2 (SGLT2) to improve renal outcomes in patients with diabetes, further promoting the emergence of renal tubulocentric research. Therefore, this review summarized the recent progress in the pathophysiology associated with involved mechanisms of renal tubules, potential tubular biomarkers with clinical application, and renal tubular factors in DKD management. The mechanism of kidney protection and impressive results from clinical trials of SGLT2 inhibitors were summarized and discussed, offering a comprehensive update on therapeutic strategies targeting renal tubules

Serum 25-hydroxyvitamin D as a predictive biomarker of clinical outcomes in patients with primary membranous nephropathy

BackgroundPrimary membranous nephropathy (PMN) is an immune-related disease with increased morbidity and the most common cause of adult nephrotic syndrome (NS). The serum 25-hydroxyvitamin D [25(OH)D)], a biomarker of vitamin D (VD) status, tends to decline in patients with kidney disease. However, the relationship between 25(OH)D and PMN is still unclear. Therefore, this study aims to clarify the association between 25(OH)D and disease severity and therapy response of PMN.MethodsA total of 490 participants diagnosed with PMN by biopsy from January 2017 to April 2022 were recruited at the First Affiliated Hospital of Nanjing Medical University. The correlations between baseline 25(OH)D and manifestations of nephrotic syndrome (NS) or seropositivity of anti-PLA2R Ab were confirmed by univariate and multivariate logistic analyses. Spearman’s correlations were used to examine the associations between baseline 25(OH)D and other clinical parameters. In the follow-up cohort, Kaplan-Meier analysis was used to assess remission outcomes among groups with low, medium, and high levels of 25(OH)D. Furthermore, the independent risk factors for non-remission (NR) were explored by COX regression analysis.ResultsAt baseline, 25(OH)D was negatively related to 24-h urinary protein and serum anti-PLA2R Ab. The lower level of baseline 25(OH)D was associated with an increased risk for the incidence of NS in PMN (model 2, OR 6.8, 95% CI 4.4, 10.7, P < 0.001) and seropositivity of anti-PLA2R Ab (model 2, OR 2.4, 95% CI 1.6, 3.7, P < 0.001). Furthermore, the lower level of 25(OH)D during follow-up was demonstrated as an independent risk factor for NR even after adjusting age, gender, MBP, 24 h UP, serum anti-PLA2R Ab, serum albumin, and serum C3 [25(OH)D (39.2–62.3 nmol/L): HR 4.90, 95% CI 1.02, 23.53 P = 0.047; 25(OH)D < 39.2 nmol/L: HR 17.52, 95% CI 4.04, 76.03 P < 0.001); vs. 25(OH)D ≥ 62.3 nmol/L]. The Kaplan-Meier survival analysis also demonstrated that the higher level of follow-up 25(OH)D had a higher possibility of remission than the lower one (log-rank test, P < 0.001).ConclusionBaseline 25(OH)D was significantly correlated with nephrotic proteinuria and seropositivity of anti-PLA2R Ab in PMN. As an independent risk factor for NR, a low level of 25(OH)D during follow-up might serve as a prognostic tool for sensitively identifying cases with a high probability of poor treatment response

Identification of dynamic model parameters for lithium-ion batteries used in hybrid electric vehicles

This paper presents an electrical equivalent circuit model for lithium-ion batteries usedfor hybrid electric vehicles (HEV). The model has two RC networks characterizing batteryactivation and concentration polarization process. The parameters of the model are identified usingcombined experimental and Extended Kalman Filter (EKF) recursive methods. The open-circuitvoltage and ohmic resistance of the battery are directly measured and calculated fromexperimental measurements, respectively. The rest of the coupled dynamic parameters, i.e. the RCnetwork parameters, are estimated using the EKF method. Experimental and simulation results arepresented to demonstrate the efficacy of the proposed circuit model and parameter identificationtechniques for simulating battery dynamics

Electronic Stability Control for Improving Stability for an Eight In-Wheel Motor-Independent Drive Electric Vehicle

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)

Analysis of Core Loss of Permanent Magnet Synchronous Machine for Vehicle Applications under Different Operating Conditions

Permanent magnet synchronous machines (PMSMs) are widely used in electric vehicles due to their high power density, high efficiency, etc. Core losses account for a significant component of the total loss in PMSMs. Therefore, it is necessary to carefully consider it when designing PMSMs according to actual scientific research project applications. This paper extracts the characteristic operating points of the PMSMs under different operating conditions at different speeds. Then a harmonic analysis of air-gap flux density, phase current, core loss was completed, and detailed comparative analysis was performed. A novel method for comprehensively analyzing the stator core loss of PMSMs for vehicles is proposed, which reveals the law of the core loss of the PMSM under Maximum-Torque-Per-Ampere (MTPA) and Space Vector Pulse Width Modulation (SVPWM). The method was verified by a prototype experiment where the actual core loss of PMSMs was measured to verify the correctness of the method. This research provides a reference for accurately predicting core loss during the forward design of PMSMs and completing core loss evaluation for existing PMSMs