Experimental and Theoretical Analysis of the Fast Charging Polymer Lithium-Ion Battery Based on Cuckoo Optimization Algorithm (COA)

Fast charging of the electric-vehicles is one of the paramount challenges in solar smart cities. This paper investigates intelligent optimization methodology to improvise the existing approaches in order to speed up the charging process whilst reducing the energy consumption without degradation in the light of the outrageous demand for lithium-ion battery in the electric vehicles (EVs). Two fitness functions are combined as the targeted objective function: energy losses (EL) and charging interval time (CIT). An intelligent optimization methodology based on Cuckoo Optimization Algorithm (COA) is implemented to the objective function for improving the charging performance of the lithium-ion battery. COA is applied through two main techniques: The Hierarchical technique (HT) and the Conditional random technique (CRT). The experimental results show that the proposed techniques permit a full charging capacity of the polymer lithium-ion battery (0 to 100% SOC) within 91 mins. Compared with the constant current-constant voltage (CCCV) technique, an improvement in the efficiency of 8% and 14.1% was obtained by the Hierarchical technique (HT) and the Conditional random technique (CRT) respectively, in addition to a reduction in energy losses of 7.783% and 10.408% respectively and a reduction in charging interval time of 18.1% and 22.45% respectively. Experimental and theoretical analyses are performed and are in good agreement on the polymer lithium-ion battery fast charging method

Electric Vehicles Lithium-Polymer Ion Battery Dynamic Behaviour Charging Identification and Modelling Scheme

Lithium-ion batteries are considered the substantial electrical storage element for electric vehicles (EVs). The battery model is the basis of battery monitoring, efficient charging, and safety management. Non-linear modelling is the key to representing the battery and its dynamic internal parameters and performance. This paper proposes a smart scheme to model the lithium-polymer ion battery while monitoring its present charging current and terminal voltage at various ambient conditions (temperature and relative humidity). Firstly, the suggested framework investigated the impact of temperature and relative humidity on the charging process using the constant current-constant voltage (CC-CV) charging protocol. This will be followed by monitoring the battery at the surrounding operating temperature and relative humidity. Hence, efficient non-linear modelling of the EV battery dynamic behaviour using the Hammerstein-Wiener (H-W) model is implemented. The H-W model is considered a black box model that can represent the battery without any mathematical equivalent circuit model which reduces the computation complexity. Finally, the model beholds the boundaries of the charging process that not affecting on the lifetime of the battery. Several dynamic models are applied and tested experimentally to ensure the effectiveness of the proposed scheme under various ambient conditions where the temperature is fixed at 40°C and the relative humidity (RH) at 35%, 52%, and 70%. The best fit using the H-W model reached 91.83% to describe the dynamic behaviour of the battery with a maximum percentage of error 0.1V which is in good agreement with the literature survey. Besides, the model has been scaled up to represent a real EV and expressed the significance of the proposed H-W model

Capturing diagnosis-timing in ICD-coded hospital data: recommendations from the WHO ICD-11 topic advisory group on quality and safety

Purpose To develop a consensus opinion regarding capturing diagnosis-timing in coded hospital data. Methods As part of the World Health Organization International Classification of Diseases-11th Revision initiative, the Quality and Safety Topic Advisory Group is charged with enhancing the capture of quality and patient safety information in morbidity data sets. One such feature is a diagnosis-timing flag. The Group has undertaken a narrative literature review, scanned national experiences focusing on countries currently using timing flags, and held a series of meetings to derive formal recommendations regarding diagnosis-timing reporting. Results The completeness of diagnosis-timing reporting continues to improve with experience and use; studies indicate that it enhances risk-adjustment and may have a substantial impact on hospital performance estimates, especially for conditions/procedures that involve acutely ill patients. However, studies suggest that its reliability varies, is better for surgical than medical patients (kappa in hip fracture patients of 0.7-1.0 versus kappa in pneumonia of 0.2-0.6) and is dependent on coder training and setting. It may allow simpler and more precise specification of quality indicators. Conclusions As the evidence indicates that a diagnosis-timing flag improves the ability of routinely collected, coded hospital data to support outcomes research and the development of quality and safety indicators, the Group recommends that a classification of ‘arising after admission' (yes/no), with permitted designations of ‘unknown or clinically undetermined', will facilitate coding while providing flexibility when there is uncertainty. Clear coding standards and guidelines with ongoing coder education will be necessary to ensure reliability of the diagnosis-timing fla

International variation in the definition of ‘main condition' in ICD-coded health data

Hospital-based medical records are abstracted to create International Classification of Disease (ICD) coded discharge health data in many countries. The ‘main condition' is not defined in a consistent manner internationally. Some countries employ a ‘reason for admission' rule as the basis for the main condition, while other countries employ a ‘resource use' rule. A few countries have recently transitioned from one of these approaches to the other. The definition of ‘main condition' in such ICD data matters when it is used to define a disease cohort to assign diagnosis-related groups and to perform risk adjustment. We propose a method of harmonizing the international definition to enable researchers and international organizations using ICD-coded health data to aggregate or compare hospital care and outcomes across countries in a consistent manner. Inter-observer reliability of alternative harmonization approaches should be evaluated before finalizing the definition and adopting it worldwid

Capturing diagnosis-timing in ICD-coded hospital data: recommendations from the WHO ICD-11 topic advisory group on quality and safety.

PURPOSE: To develop a consensus opinion regarding capturing diagnosis-timing in coded hospital data. METHODS: As part of the World Health Organization International Classification of Diseases-11th Revision initiative, the Quality and Safety Topic Advisory Group is charged with enhancing the capture of quality and patient safety information in morbidity data sets. One such feature is a diagnosis-timing flag. The Group has undertaken a narrative literature review, scanned national experiences focusing on countries currently using timing flags, and held a series of meetings to derive formal recommendations regarding diagnosis-timing reporting. RESULTS: The completeness of diagnosis-timing reporting continues to improve with experience and use; studies indicate that it enhances risk-adjustment and may have a substantial impact on hospital performance estimates, especially for conditions/procedures that involve acutely ill patients. However, studies suggest that its reliability varies, is better for surgical than medical patients (kappa in hip fracture patients of 0.7-1.0 versus kappa in pneumonia of 0.2-0.6) and is dependent on coder training and setting. It may allow simpler and more precise specification of quality indicators. CONCLUSIONS: As the evidence indicates that a diagnosis-timing flag improves the ability of routinely collected, coded hospital data to support outcomes research and the development of quality and safety indicators, the Group recommends that a classification of 'arising after admission' (yes/no), with permitted designations of 'unknown or clinically undetermined', will facilitate coding while providing flexibility when there is uncertainty. Clear coding standards and guidelines with ongoing coder education will be necessary to ensure reliability of the diagnosis-timing flag

International variation in the definition of 'main condition' in ICD-coded health data

Hospital-based medical records are abstracted to create International Classification of Disease (ICD) coded discharge health data in many countries. The 'main condition' is not defined in a consistent manner internationally. Some countries employ a 'reason for admission' rule as the basis for the main condition, while other countries employ a 'resource use' rule. A few countries have recently transitioned from one of these approaches to the other. The definition of 'main condition' in such ICD data matters when it is used to define a disease cohort to assign diagnosis-related groups and to perform risk adjustment. We propose a method of harmonizing the international definition to enable researchers and international organizations using ICD-coded health data to aggregate or compare hospital care and outcomes across countries in a consistent manner. Inter-observer reliability of alternative harmonization approaches should be evaluated before finalizing the definition and adopting it worldwide

A World Health Organization field trial assessing a proposed ICD-11 framework for classifying patient safety events.

To assess the utility of the proposed World Health Organization (WHO)'s International Classification of Disease (ICD) framework for classifying patient safety events. Independent classification of 45 clinical vignettes using a web-based platform. The WHO's multi-disciplinary Quality and Safety Topic Advisory Group. The framework consists of three concepts: harm, cause and mode. We defined a concept as 'classifiable' if more than half of the raters could assign an ICD-11 code for the case. We evaluated reasons why cases were nonclassifiable using a qualitative approach. Harm was classifiable in 31 of 45 cases (69%). Of these, only 20 could be classified according to cause and mode. Classifiable cases were those in which a clear cause and effect relationship existed (e.g. medication administration error). Nonclassifiable cases were those without clear causal attribution (e.g. pressure ulcer). Of the 14 cases in which harm was not evident (31%), only 5 could be classified according to cause and mode and represented potential adverse events. Overall, nine cases (20%) were nonclassifiable using the three-part patient safety framework and contained significant ambiguity in the relationship between healthcare outcome and putative cause. The proposed framework enabled classification of the majority of patient safety events. Cases in which potentially harmful events did not cause harm were not classifiable; additional code categories within the ICD-11 are one proposal to address this concern. Cases with ambiguity in cause and effect relationship between healthcare processes and outcomes remain difficult to classify

Enhanced capture of healthcare-related harms and injuries in the 11th revision of the International Classification of Diseases (ICD-11).

The World Health Organization (WHO) plans to submit the 11th revision of the International Classification of Diseases (ICD) to the World Health Assembly in 2018. The WHO is working toward a revised classification system that has an enhanced ability to capture health concepts in a manner that reflects current scientific evidence and that is compatible with contemporary information systems. In this paper, we present recommendations made to the WHO by the ICD revision's Quality and Safety Topic Advisory Group (Q&S TAG) for a new conceptual approach to capturing healthcare-related harms and injuries in ICD-coded data. The Q&S TAG has grouped causes of healthcare-related harm and injuries into four categories that relate to the source of the event: (a) medications and substances, (b) procedures, (c) devices and (d) other aspects of care. Under the proposed multiple coding approach, one of these sources of harm must be coded as part of a cluster of three codes to depict, respectively, a healthcare activity as a 'source' of harm, a 'mode or mechanism' of harm and a consequence of the event summarized by these codes (i.e. injury or harm). Use of this framework depends on the implementation of a new and potentially powerful code-clustering mechanism in ICD-11. This new framework for coding healthcare-related harm has great potential to improve the clinical detail of adverse event descriptions, and the overall quality of coded health data