关于Semigroups of Linear Operators and Applications to Partial Differential Equations的两个注解

Due to increasing concerns about global warming, greenhouse gas emissions, and the depletion of fossil fuels, the electric vehicles (EVs) receive massive popularity due to their performances and efficiencies in recent decades. EVs have already been widely accepted in the automotive industries considering the most promising replacements in reducing CO2 emissions and global environmental issues. Lithium-ion batteries have attained huge attention in EVs application due to their lucrative features such as lightweight, fast charging, high energy density, low self-discharge and long lifespan. This paper comprehensively reviews the lithium-ion battery state of charge (SOC) estimation and its management system towards the sustainable future EV applications. The significance of battery management system (BMS) employing lithium-ion batteries is presented, which can guarantee a reliable and safe operation and assess the battery SOC. The review identifies that the SOC is a crucial parameter as it signifies the remaining available energy in a battery that provides an idea about charging/discharging strategies and protect the battery from overcharging/over discharging. It is also observed that the SOC of the existing lithium-ion batteries have a good contribution to run the EVs safely and efficiently with their charging/discharging capabilities. However, they still have some challenges due to their complex electro-chemical reactions, performance degradation and lack of accuracy towards the enhancement of battery performance and life. The classification of the estimation methodologies to estimate SOC focusing with the estimation model/algorithm, benefits, drawbacks and estimation error are extensively reviewed. The review highlights many factors and challenges with possible recommendations for the development of BMS and estimation of SOC in next-generation EV applications. All the highlighted insights of this review will widen the increasing efforts towards the development of the advanced SOC estimation method and energy management system of lithium-ion battery for the future high-tech EV applications.

A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations

Critical review of the methods for monitoring of lithium-ion batteries in electric and hybrid vehicles

With the rapid development of new energy electric vehicles and smart grids, the demand for batteries is increasing. The battery management system (BMS) plays a crucial role in the battery-powered energy storage system. This paper presents a systematic review of the most commonly used battery modeling and state estimation approaches for BMSs. The models include the physics-based electrochemical models, the integral and fractional order equivalent circuit models, and data-driven models. The state estimation approaches are analyzed from the perspectives of remaining capacity and energy estimation, power capability prediction, lifespan and health prognoses, and other crucial indexes in BMS. This present paper, through the analysis of literature, includes almost all states in the BMS. The estimation approaches of state-of-charge (SOC), state-of-energy (SOE), state-of-power (SOP), state-of-function (SOF), state-of-health (SOH), remaining useful life (RUL), remaining discharge time (RDT), state-of-balance (SOB), and state-of-temperature (SOT) are reviewed and discussed in a systematical way. Moreover, the challenges and outlooks of the research on future battery management are disclosed, in the hope of providing some inspirations to the development and design of the next-generation BMSs.

A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems

Thank you very much for downloading introduction to infinite dimensional linear systems theory. As you may know, people have search numerous times for their favorite novels like this introduction to infinite dimensional linear systems theory, but end up in malicious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they juggled with some harmful bugs inside their laptop.

Introduction To Infinite Dimensional Linear Systems Theory

Battery state of the charge estimation using Kalman filtering

Lithium-ion batteries are used to store energy in electric vehicles. State of charge (SOC) is an important quantity of the battery cells that need to be estimated using limited measurements. In this paper, SOC estimation via an electrochemical model, a physics-based model, is considered. For lithium iron phosphate cells, a variable solid-state diffusivity model provides significantly more accuracy, but this complicates the model further. A previously obtained, simplified but still a physics-based model is used in this paper. An extended Kalman filter (KF)-based adaptive observer is designed via a low-order approximation of this electrochemical model. The predictions of the estimator are compared with the experimental data in simulations. The simulations are efficient and more accurate than a standard KF.

State-of-Charge Estimation Using an EKF-Based Adaptive Observer

Purpose Rose bengal (RB)-photosensitized protein crosslinking has been proposed for several applications in the eye. This study identifies oxygen-dependent and oxygen-independent mechanistic pathways in cornea for RB-photosensitized crosslinking to enhance its efficiency for ocular treatments. Methods Rabbit corneas ex vivo were stained with 1 mM RB and irradiated at 532 nm. RB photobleaching, measured by spectrophotometry and linear tensile strength testing, were performed with and without oxygen present. The effects of sodium azide, D2O, arginine, and ascorbate were used to discriminate between mechanisms involving energy transfer (forming singlet oxygen) and electron transfer (forming radical ions). The influence of corneal depth on RB photobleaching was determined using inclined corneal incisions. Results RB photobleaching was greater in the presence than the absence of oxygen, enhanced by D2O and partially inhibited by azide, indicating a singlet oxygen pathway. Photobleaching without oxygen was enhanced by arginine and ascorbate and accompanied by a shift in the absorption to shorter wavelengths, suggesting that electron transfer initiates RB photodecomposition. The RB-photosensitized tensile strength increase in air was enhanced by D2O and inhibited by azide. In an O2-free environment, arginine was required for an increase in tensile strength, which matched that attained by irradiation in air without arginine, suggesting an efficient electron transfer pathway. Rapid photobleaching was observed below 80 to 120 μm only when arginine was present. Conclusions These results indicate that RB photosensitizes crosslinking in cornea by both singlet oxygen and electron transfer mechanisms and that adding enhancers may increase the efficiency of this treatment.

Enhancing Rose Bengal-Photosensitized Protein Crosslinking in the Cornea.

Background The early diagnosis of colorectal cancer (CRC) is associated with improved survival rates, and development of novel non-invasive, sensitive, and specific diagnostic tests is highly demanded. The objective of this paper was to identify commonly circulating microRNA (miRNA) biomarkers for use in CRC diagnosis. Methods An artificial neural network (ANN) model was proposed in this work. Among miRNAs retrieved from the Gene Expression Omnibus dataset, four miRNAs with the best miRNA score were selected by ANN units. Results The simulation results showed that the designed ANN model could accurately classify the sample data into cancerous or non-cancerous. Furthermore, based on the results of evaluated ANN model, the area under the ROC curve (AUC) of the designed ANN model as well as the regression coefficient between the output of the ANN and the expected output was one. The confusion matrix of the ANN model indicated that all non-cancerous patients were predicted as normal, and the cancerous patients as cancerous. Conclusion Our findings suggest that the improved model can be used as a robust prediction toolbox for cancer diagnosis. In conclusion, by using ANN, circulatory miRNAs can be used as a non-invasive, sensitive and specific diagnostic marker.

Application of Artificial Neural Network in miRNA Biomarker Selection and Precise Diagnosis of Colorectal Cancer

Recently, the development of medical instrumentation has advanced less invasive therapeutic operations. Micro device navigation through the human body, especially blood vessels, is an important part of minimally invasive techniques. Remote actuation is critical in order to manipulate the micro object inside the body. To achieve remote control within the cardiovascular system, magnetic propulsion offers an advantage over conventional actuation methods eliminating carry-on power supplies. A general magnetic propulsion system is composed of several electromagnets assembled with different orientations and positions. For remote actuation, the magnetic field produced plays an important role in initiating appropriate induction on micro devices. The effect of the electromagnets' arrangement is studied in this paper. Moreover, an optimization criterion is introduced here by which the performance of two effective but different structures is compared. Finally, the optimum structure, which improves actuator efficiency in micro scale applications, is discussed.

Sepideh Afshar

Papers

Battery state of the charge estimation using Kalman filtering

State-of-Charge Estimation Using an EKF-Based Adaptive Observer

Enhancing Rose Bengal-Photosensitized Protein Crosslinking in the Cornea.

Application of Artificial Neural Network in miRNA Biomarker Selection and Precise Diagnosis of Colorectal Cancer

Optimal Configuration for Electromagnets and Coils in Magnetic Actuators