Evaluation of Various Offline and Online ECM Parameter Identification Methods of Lithium-Ion Batteries in Underwater Vehicles.

For underwater vehicles, the state of charge (SOC) of battery is often used to guide the optimal allocation of energy. An accurate SOC estimation can improve work efficiency and reliability of underwater vehicles. Model-based SOC estimation methods are still mainstream routes used in practical applications. Hence, accurate battery models are highly desirable, which depends not only on the circuit structure but also on the circuit parameters. Four-parameter identification algorithms, offline mechanism-based and least squared (LS) methods, as well as online recursive least-squares with forget factor (FFRLS) and extended Kalman filter (EKF) methods were analyzed in terms of SOC estimation under three different conditions. The results revealed that in the case without any disturbance, the predicted SOCs based on four-parameter identification circuits fitted well with the reference. Moreover, it is remarkable that the LS offline methods work better than the FFRLS online routes. In addition, the robustness has also been accessed through the other two conditions, i.e., measurement data with disturbance and initial SOC value with deviation. The results showed that maximum errors of SOC estimation based on the EKF approach are significantly lower than those of the other methods, and the values are 0.51% and 0.20%, respectively. Thus, the circuit model based on the EKF parameter identification approach possessed a stronger anti-interference performance during the SOC estimation process. This research can provide corresponding theoretical support on ECM parameter identification for lithium-ion batteries in underwater vehicles.

Exploring metabolic and inflammatory abnormalities in rheumatoid arthritis patients developing stroke disease: a case-control study using electronic medical record data in northern China.

OBJECTIVES: Intend to investigate the roles of serum lipids, inflammatory markers, and serological status in rheumatoid arthritis and stroke patients by using case-control study. MATERIALS AND METHODS: Clinical data were retrieved from the electronic medical record of the First Affiliated Hospital of China Medical University during January 2011 to March 2018. The obtained data were categorized into case groups and three control groups, in the ratios of 1:2, respectively, with all matching age and gender. Multinomial logistic regression analysis and restricted cubic spline were conducted examining the associations between serum lipids, inflammatory markers, serological status, and the risk of stroke among RA patients. RESULTS: The present studies included 1057 study subjects. The elevated ESR, LDL-C levels, and much higher CRP levels ≥ 230 mg/L were independent risk factors for RA patients in developing stroke. Furthermore, we found that ESR and LDL-C levels could exhibit a linear association with the risk of comorbid stroke while CRP level had a nonlinearity association with stroke risk among RA patients. CONCLUSIONS: A close monitoring is required for RA patients with dyslipidemia and elevated inflammatory markers, and the primary stroke preventive strategies should be directed against these risk factors.

A study of the effect of clinical washing decontamination process on corrosion resistance of Martensitic Stainless Steel 420.

Corrosion of surgical instruments provides a seat for contamination and prevents proper sterilisation, placing both patients and medical staff at risk of infection. Corrosion can also compromise the structural integrity of instruments and lead to mechanical failure in use. It is essential to understand the various factors affecting corrosion resistance of surgical instruments and how it can be minimised.This paper investigates the effect on corrosion resistance from the clinical washing decontamination (WD) process, specifically by studying the changes in surface roughness and Cr/Fe ratio. Results indicate that the WD process provides a positive effect on smooth polished samples, while a lesser positive effect was observed on rough reflection reduced samples.