Model Predictive Control for Connected Hybrid Electric Vehicles

This paper presents a new model predictive control system for connected hybrid electric vehicles to improve fuel economy. The new features of this study are as follows. First, the battery charge and discharge profile and the driving velocity profile are simultaneously optimized. One is energy management for HEV for Pbatt; the other is for the energy consumption minimizing problem of acc control of two vehicles. Second, a system for connected hybrid electric vehicles has been developed considering varying drag coefficients and the road gradients. Third, the fuel model of a typical hybrid electric vehicle is developed using the maps of the engine efficiency characteristics. Fourth, simulations and analysis (under different parameters, i.e., road conditions, vehicle state of charge, etc.) are conducted to verify the effectiveness of the method to achieve higher fuel efficiency. The model predictive control problem is solved using numerical computation method: continuation and generalized minimum residual method. Computer simulation results reveal improvements in fuel economy using the proposed control method

Efficacy and safety of triazavirin therapy for coronavirus disease 2019 : A pilot randomized controlled trial

Acknowledgements: We are deeply grateful to the front-line clinicians who participated in the study while directly fighting the epidemic. This study was supported by the Chinese Academy of Engineering Projects for COVID-19 (2020-KYGG-01-04) and Heilongjiang Province Urgent Project-6 for COVID-19. Data and safety monitoring board members of this trial included Kang Li, Yong Zhang, Songjiang Liu, and Yaohui Shi.Peer reviewedPublisher PD

Performance of a Nonlinear Real-Time Optimal Control System for HEVs/PHEVs during Car Following

This paper presents a real-time optimal control approach for the energy management problem of hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs) with slope information during car following. The new features of this study are as follows. First, the proposed method can optimize the engine operating points and the driving profile simultaneously. Second, the proposed method gives the freedom of vehicle spacing between the preceding vehicle and the host vehicle. Third, using the HEV/PHEV property, the desired battery state of charge is designed according to the road slopes for better recuperation of free braking energy. Fourth, all of the vehicle operating modes engine charge, electric vehicle, motor assist and electric continuously variable transmission, and regenerative braking, can be realized using the proposed real-time optimal control approach. Computer simulation results are shown among the nonlinear real-time optimal control approach and the ADVISOR rule-based approach. The conclusion is that the nonlinear real-time optimal control approach is effective for the energy management problem of the HEV/PHEV system during car following

COVID-19 infection epidemic: the medical management strategies in Heilongjiang Province, China

In late December 2019, an outbreak of the 2019-novel coronavirus (COVID-19) caused a substantial public health crisis in Wuhan, China, and then expeditiously spread all over China [1,2,3]. As of March 4, 2020, 80,409 cases of COVID-19 had been confirmed in mainland China [4]. While in Heilongjiang province, which locates in northeastern China with 38.24 million residents and an area of 473,000 km2, all of its 13 cities were affected, making it one of the most serious areas for the outbreak of COVID-19 in China. Up to February 23, 2020, there were 480 confirmed cases of COVID-19; however, no newly diagnosed cases since then. Most of the infected patients were male and there were 13 deaths (2.7%). A series of protocols had been established since the first confirmed case emerged, and we herein summarize our experience from Heilongjiang province in dealing with COVID-19

Predictive control strategies for energy saving of hybrid electric vehicles based on traffic light information

As the conventional control method for hybrid electric vehicle doesn’t consider the effect of known traffic light information on the vehicle energy management, this paper proposes a model predictive control intelligent optimization strategies based on traffic light information for hybrid electric vehicles. By building the simplified model of the hybrid electric vehicle and adopting the continuation/generalized minimum residual method, the model prediction problem is solved. The simulation is conducted by using MATLAB/Simulink platform. The simulation results show the effectiveness of the proposed model of the traffic light information, and that the proposed model predictive control method can improve fuel economy and the real-time control performance significantly. The research conclusions show that the proposed control strategy can achieve optimal control of the vehicle trajectory, significantly improving fuel economy of the vehicle, and meet the system requirements for the real-time optimal control

Fatigue Crack Calculation of Steel Structure Based on the Improved McEvily Model

Numerous fatigue crack mechanism models have been proposed based on an in-depth study of material fatigue mechanisms and engineering requirements. However, due to many of the parameters in these models being difficult to determine, their application to engineering is limited. The fatigue crack of the steel structure was calculated based on the improved McEvily model. To begin, based on the theory of linear elastic fracture mechanics, some parameters of the McEvily fatigue crack growth model were deduced and determined by using more reasonable assumptions and empirical formulas. Second, the effectiveness of the improved McEvily fatigue crack growth model was proven by comparison to the results of the improved model with the classical Paris model. Finally, the improved McEvily model was applied to practical engineering, and the typical fatigue crack of steel structure was selected and compared with the results of the Paris model and nominal stress method to verify its feasibility in engineering. The results reveal that the application conditions of the improved McEvily model can be extended from laboratory conditions to practical engineering, and its accuracy is better than that of the Paris model, which can well evaluate the fatigue crack life of steel structures

Fatigue Crack Calculation of Steel Structure Based on the Improved McEvily Model

Numerous fatigue crack mechanism models have been proposed based on an in-depth study of material fatigue mechanisms and engineering requirements. However, due to many of the parameters in these models being difficult to determine, their application to engineering is limited. The fatigue crack of the steel structure was calculated based on the improved McEvily model. To begin, based on the theory of linear elastic fracture mechanics, some parameters of the McEvily fatigue crack growth model were deduced and determined by using more reasonable assumptions and empirical formulas. Second, the effectiveness of the improved McEvily fatigue crack growth model was proven by comparison to the results of the improved model with the classical Paris model. Finally, the improved McEvily model was applied to practical engineering, and the typical fatigue crack of steel structure was selected and compared with the results of the Paris model and nominal stress method to verify its feasibility in engineering. The results reveal that the application conditions of the improved McEvily model can be extended from laboratory conditions to practical engineering, and its accuracy is better than that of the Paris model, which can well evaluate the fatigue crack life of steel structures

Lactate up-regulates the expression of PD-L1 in kidney and causes immunosuppression in septic Acute Renal Injury

Background: This study aims to explore the mechanism of immunosuppression in septic Acute Renal Injury (AKI) and the role of programmed death-1 (PD-1/PD-L1) pathway in septic AKI. Methods: This study established a septic AKI model by Cecal ligation and puncture (CLP) in C57/B6 mice, ELISA was used to test the level of lactate and creatinine in serum, blood was collected for flow cytometry and kidney samples for Western blot analyses. This study further analyzed the expression of PD-L1 in kidney and the expression of PD-1 in CD4+, CD8+ T cell, and the number of CD3+ T cells to identify apoptosis in T cells in the blood. Results: The CLP sepsis model induced AKI in C57/B6 mice; The expression of PD-1 and PD-L1 were increased in septic AKI mice; PD-1/PD-L1 induced apoptosis in T cells: the number of lymphocytes decreased by 64%, while the number of CD3+ T cells decreased by 27% compared with the sham group; Results also indicated that lactate up-regulates expression of PD-L1 in the kidney. Conclusions: Lactate activated PD-1/PD-L1 pathway can induce immunosuppression by inducing apoptosis in lymphocytes in septic AKI. Moreover, blocking the receptor of lactate or PD-1/PD-L1 might be a new therapy for septic AKI