Inequalities in levels of health between regions within a country are frequently regarded as a problem. Zimbabwe is characterised by poor and unequal conditions of health (both the state of people’s health and health services). The health system of the country shows severe spatial inequalities that are manifested at provincial, district and even local levels. This research therefore examines and analyses the spatial inequalities and temporal variation of health conditions in Zimbabwe. Composite indices were used to determine the people’s state of health in Zimbabwe. Administrative districts were ranked according to the level of people’s state of health. Cluster analysis was also performed to demarcate administrative districts according the level of health service provision. Districts with minimum difference were demarcated in a single cluster. Clusters were delineated using data on patterns of diseases and health and such clusters were used to demarcate the country’s spatial health system according to the Adapted Epidemiological Transition Model. This was used to evaluate the applicability of the model to Zimbabwe. It emerged from the research that generally the country’s health conditions are poor and the health system is characterised by severe spatial inequalities. Some districts are experiencing poor health service provision and serious health challenges and are still in the age of pestilence and famine but others have good health service provision as well as highly developed health conditions and are in the age degenerative diseases of the epidemiological transition model. It further emerged that the country’s health has been evolving with signs of improvement since the 1990s. Recommendations were made regarding possible adjustment to previous strategies and policies used in Zimbabwe, for the development of the health system of the country. New strategies were also recommended for the improvement of the health system of the country. Some proposals are made for further research on the spatial development of health in the country. / Geography / D. Litt et. Phil. (Geography)

The topic of the thesis is {\clqq} The examination of state of health of citizens for the purposes of social welfare benefits.{\crqq} Medical statement sevice ensures this activity, which has a wide medical, social, employment and economic importance. On 1st January 2006 the first instance medical statement service was divided into the insurance and non-insurance system. OSSZ and ČSSZ continues providing examinations for the insurance systems while the examination for the non-insurance system is carried out by physicians of the newly created examination services of employment agencies. The paper aims at analysing the so far experience of the medical statement service after the division into the insurance and non-insurance system. I presume that the division of the medical statement service and its transformation have been effective. I have dealt with the medical statement system in the most wide context. In the theoretical part I have concentrated on historical development of the medical statement service, on its system and the scope of activity of the medical statement service and I did not omit the examination of state of health of citizens for the purposes of the social welfare systems. In the practical part I concentrated on physicians carrying out medical statements for employment agencies and district administrations of social welfare, on their feelings, opinions on the reorganization of the medical statement service in 2006. The research was carried out in Central Bohemia region with the view to evaluate the division of the medical statement service in the insurance and non-insurance system. A quantitave attitude was chosen for this research usingt the questionnaire method. Two types of questionnaires were handed out: for physicians of the medical statement service of employment agencies and for physicians of medical statement service of district administration of social welfare system. In total there were 40 questionnaires handed out to the physicians of medical statement service of district administration of social welfare system and 25 to the physicians of the medical statement service of employment agencies. 34 (100%) questionnaires were used filled by the employment agencies physicians and 16 (100%) questionnaires filled by the physicians of the district administration of social welfare system. I chose the graph form to process the research part of the paper. The principal hypothesis was confirmed. For both the physicians of the medical statement service of employment agencies and physicians of medical statement service of district administration of social welfare system was proved that the division of the medical statement service into the insurance and non-insurance system was effective. Further activities within the organization of the medical statement service should endeavour to depict small discrepancies and to ensure a continuous improvement of the system.

Internal environment is an environment in which we spend most of our time. That is the reason why it has a significant impact on our physical health and mental wellbeing. Yet, there are a number of factors that may pose health risks; and that is why this issue should not be underestimated. The objective of the diploma thesis at hand is to assess the results as they were recorded in a targeted public health supervision focused on the guality of internal environment. The said state supervision was imposed by the Chief Public Health Officer of the Czech Republic of 14th March 2007 on Regional Hygiene Authorities including Prague Hygiene Authority, directors of Regional Hygiene Authorities, and directors of health institutions. Based on the reports on measurements of selected quality indicators in the internal environment of the Ice Arena in České Budějovice and their outcomes regarding the quality of the internal environment, the author expects to come to a conclusion which would confirm that measures taken due to the public health supervision have been sufficient in terms of efficiency. The given objective has been confirmed in the chapter ?Outcomes?. The theoretical part of the diploma thesis observes findings dealing with atmosphere in general, internal environment, and state public health supervision. The research part of the thesis was completed employing a qualitative research. Methods employed in data collection were observation and documents analysis. The data collection was carried out by secondary data analysis. All data were gained, firstly, from the results of the measurements carried out by the Hygiene Authorities of the Health Institution after these had been assessed (in 2007 under the auspices of the Health Institute based in České Budějovice, and in 2011 under the auspices of the Health Institute based in Plzeň), and, secondly, studiyng in detail related file documents provided by the Regional Hygiene Authority of the Region of South Bohemia based in České Budějovice. Unfortunately, there are no papers or books available on the topic to compare the thesis with. This thesis may be utilized by professionals at the Regional Hygiene Authority of the Region of South Bohemia based in České Budějovice during further research, and even by general public when providing information on the quality of internal environment of this important sport facility.

Electric vehicles have received substantial attention in the past few years since they provide a more sustainable, efficient, and greener transportation alternative in comparison to conventional fossil-fuel powered vehicles. Lithium-Ion batteries represent the most important component in the electric vehicle powertrain and thus require accurate monitoring and control. Many challenges are still facing the mass market production of electric vehicles; these challenges include battery cost, range anxiety, safety, and reliability. These challenges can be significantly mitigated by incorporating an efficient battery management system. The battery management system is responsible for estimating, in real-time, the battery state of charge, state of health, and remaining useful life in addition to communicating with other vehicle components and subsystems. In order for the battery management system to effectively perform these tasks, a high-fidelity battery model along with an accurate, robust estimation strategy must work collaboratively at various power demands, temperatures, and states of life. Lithium ion batteries are considered in this research. For these batteries, electrochemical models represent an attractive approach since they are capable of modeling lithium diffusion processes and track changes in lithium concentrations and potentials inside the electrodes and the electrolyte. Therefore, electrochemical models provide a connection to the physical reactions that occur in the battery thus favoured in state of charge and state of health estimation in comparison to other modeling techniques. The research presented in this thesis focuses on advancing the development and implementation of battery models, state of charge, and state of health estimation strategies. Most electrochemical battery models have been verified using simulation data and have rarely been experimentally applied. This is because most electrochemical battery model parameters are considered proprietary information to their manufacturers. In addition, most battery models have not accounted for battery aging and degradation over the lifetime of the vehicle using real-world driving cycles. Therefore, the first major contribution of this research is the formulation of a new battery state of charge parameterization strategy. Using this strategy, a full-set of parameters for a reduced-order electrochemical model can be estimated using real-world driving cycles while accurately calculating the state of charge. The developed electrochemical model-based state of charge parameterization strategy depends on a number of spherical shells (model states) in conjunction with the final value theorem. The final value theorem is applied in order to calculate the initial values of lithium concentrations at various shells of the electrode. Then, this value is used in setting up constraints for the optimizer in order to achieve accurate state of charge estimation. Developed battery models at various battery states of life can be utilized in a real-time battery management system. Based on the developed models, estimation of the battery critical surface charge using a relatively new estimation strategy known as the Smooth Variable Structure Filter has been effectively applied. The technique has been extended to estimate the state of charge for aged batteries in addition to healthy ones. In addition, the thesis introduces a new battery aging model based on electrochemistry. The model is capable of capturing battery degradation by varying the effective electrode volume, open circuit potential-state of charge relationship, diffusion coefficients, and solid-electrolyte interface resistance. Extensive experiments for a range of aging scenarios have been carried out over a period of 12 months to emulate the entire life of the battery. The applications of the proposed parameterization method combined with experimental aging results significantly improve the reduced-order electrochemical model to adapt to various battery states of life. Furthermore, online and offline battery model parameters identification and state of charge estimation at various states of life has been implemented. A technique for tracking changes in the battery OCV-R-RC model parameters as battery ages in addition to estimation of the battery SOC using the relatively new Smooth Variable Structure Filter is presented. The strategy has been validated at both healthy and aged battery states of life using driving scenarios of an average North-American driver. Furthermore, online estimation of the battery model parameters using square-root recursive least square (SR-RLS) with forgetting factor methodology is conducted. Based on the estimated model parameters, estimation of the battery state of charge using regressed-voltage-based estimation strategy at various states of life is applied. The developed models provide a mechanism for combining the standalone estimation strategy that provide terminal voltage, state of charge, and state of health estimates based on one model to incorporate these different aspects at various battery states of life. Accordingly, a new model-based estimation strategy known as the interacting multiple model (IMM) method has been applied by utilizing multiple models at various states of life. The method is able to improve the state of charge estimation accuracy and stability, when compared with the most commonly used strategy. This research results in a number of novel contributions, and significantly advances the development of robust strategies that can be effectively applied in real-time on-board of a battery management system. / Thesis / Doctor of Philosophy (PhD)

No description available.

The electrification within the automotive industry goes faster than ever, which drives an increased demand for more knowledge about batteries. Vehicle manufacturers should be able to tell how long the batteries will last and have a service program for electrified vehicles, just as there is for traditional, fuel-driven ones. Scania is in the process of developing new service methods for their hybrids and fully electrified vehicles where this thesis has been a part of this development by investigating the possibilities of having a workshop test to measure the capacity of the propulsion batteries.  During the thesis, essential parameters for cycling the batteries and measure the capacity with high accuracy have been identified and investigated by conducting lab tests. In parallel to defining the properties of a successful capacity measurement, the implementation of such a measurement at a workshop has been studied alongside a brief discussion about scheduling strategies. Conducting a capacity measurement in a workshop environment introduce new challenges, and the critical question arises, how long can the capacity measurement take? It is identified that the state of charge window size, the temperature, and the relaxation time are essential parameters to control. From the experimental part of the thesis, it can be concluded that the start temperature should lay in the range of 15-25 °C with a relaxation time of 5-10 minutes providing a satisfying accuracy. A SOC window size of 20-80% seems to be the most optimal balance between time spent and accuracy in the measurement. Furthermore, it is identified that the workshop's equipment is heavily influencing the time it takes to conduct a test. It is concluded that it is necessary to be able to charge and discharge the batteries. / Elektrifieringen av fordons industrin går snabbare än någonsin, vilket driver en högre efterfrågan på mer kunskap om batterier. Fordons tillverkare ska kunna redogöra för hur länge batterierna kan användas och ha ett service program för elektrifierade fordon, likt det som redan finns för traditionella, bränsledrivna fordon. Scania håller på att utveckla nya service metoder för sina hybrider och elektriska fordon där detta examensarbete har varit en del av denna utveckling genom att undersöka möjligheterna kring en verkstadsmetod för att mäta kapaciteten hos framdrivnings batterier.  Under examensarbetet har väsentliga parametrar för cykling av batterier och mätning av kapacitet med hög noggrannhet identifierats och undersökts med laboratorietester. Parallellt med arbetet för att definiera egenskaperna hos en precis kapacitets mätning har implementationen av en sådan mätning i en verkstad studerats tillsammans med en kort diskussion om strategier för schemaläggning av dessa tester. Det introducerar nya utmaningar att utföra kapacitets mätningen i en verkstad och den viktiga frågan uppstår, hur lång tid tar en sådan kapacitets mätning? Det har identifieras att SOC fönster storleken, temperaturen och relaxeringstiden är essentiella parametrar att kontrollera. Slutsatserna är att temperaturen bör ligga i intervallet 15-25 °C med en relaxeringstid på 5-10 minuter ger en tillfredställande noggrannhet. Ett SOC fönster motsvarande 20-80% är förefaller vara den mest optimala i avvägningen mellan tidsåtgång och precision. Vidare kan den tillgängliga utrustningen på verkstaden pekas ut som en starkt påverkande faktor till tiden det tar att utföra ett sådant verkstadstest.

Due to the large share of production costs, the lifespan of an electric vehicle’s (EV) lithium-ion traction battery should be as long as possible. The optimisation of the EV’s operating strategy with regard to battery life requires a regular evaluation of the battery’s state-of-health (SOH). Yet the SOH, the remaining battery capacity, cannot be measured directly through sensors but requires the elaborate conduction of special characterisation tests. Considering the limited number of test facilities as well as the rapidly growing number of EVs, time-efficient and scalable SOH estimation methods are urgently needed and are the object of investigation in this work. The developed virtual SOH experiment originates from the incremental capacity measurement and solely relies on the commonly logged battery management system (BMS) signals to train the digital battery twins. The first examined dataset with identical load profiles for new and aged battery state serves as proof of concept. The successful SOH estimation based on the second dataset that consists of varying load profiles with increased complexity constitutes a step towards the application on real driving cycles. Assuming that the load cycles contain pauses and start from the fully charged battery state, the SOH estimation succeeds either through a steady shift of the load sequences (variant one) with an average deviation of 0.36% or by random alignment of the dataset’s subsequences (variant two) with 1.04%. In contrast to continuous capacity tests, the presented framework does not impose restrictions to small currents. It is entirely independent of the prevailing and unknown ageing condition due to the application of battery models based on the novel encoder–decoder architecture and thus provides the cornerstone for a scalable and robust estimation of battery capacity on a pure data basis.

The continuous monitoring of the state-of-health (SOH) of electric vehicles (EV) represents a problem with great research relevance due to the time-consuming battery cycling and capacity measurements that are usually required to create a SOH estimation model. Instead of the widely used approach of modelling the battery’s degradation behaviour with as little cycling effort as possible, the applied SOH monitoring approach is the first of its kind that is solely based on commonly logged battery management system (BMS) signals and does not rely on tedious capacity measurements. These are used to train the digital battery twins, which are subsequently subjected to virtual capacity tests to estimate the SOH. In this work, transfer-learning is applied to increase the data and computational efficiency of the digital battery twins training process to facilitate a real-world application as it enables SOH estimation for unknown ageing states due to the selective parameter initialisation at less than a tenth of the common training time. However, the successful SOH estimation with a mean SOH deviation of 0.05% using transfer-learning still requires the presence of pauses in the dataset. Meta-learning extends the idea of transfer-learning as the baseline model simultaneously takes several ageing states into account. Learning the basic battery-electric behaviour it is forced to preserve a certain level of uncertainty at the same time, which seems crucial for the successful fine-tuning of the model parameters based on three pause-free load profiles resulting in a mean SOH deviation of 0.85%. This optimised virtual SOH experiment framework provides the cornerstone for a scalable and robust estimation of the remaining battery capacity on a pure data basis.

The prediction of a company's financial health is of critical importance to a variety of stakeholders ranging from auditors, creditors, customers, employees, financial institutions and investors through to management. There has been considerable research in this field, ranging from the univariate dichotomous approach of Beaver (1966) to the multivariate multi-state approaches of Lau (1987) and Ward (1994). All of the South African studies namely, Strebel and Andrews (1977), Daya (1977), De La Rey (1981), Clarke et al (1991) and Court et al (1999), and even, Lukhwareni's (2005) four separate models, were dichotomous in nature providing either a "Healthy" or a "Failed" state; or a "Winner" or "Loser" as in the latter case. Notwithstanding, all of these models would be classified as first stage, initial screening models. This study has focused on following a two stage approach to identifying (first stage) and analysing (second stage) the States of Health in a company. It has not adopted the rigid "Healthy" or "Failed" dichotomous methodology. For the first stage, three-state models were developed classifying a company as Healthy, Intermittent or Distressed. Both three year and five year Profit after Tax (PAT) averages for Real Earnings Growth (REG) calculations were used to determine the superior definition for the Intermittent state; with the latter coming out as superior. Models were developed for the current year (Yn), one (Yn-1), two (Yn-2) and three years (Yn-3) forward using a Test sample of twenty companies and their predictive accuracy determined by using a Holdout sample of twenty-two companies and all their data points or years of information. The statistical methods employed were a Naïve model using the simple Shareholder Value Added (SVA) ratio, CHAID and MDA, with the latter providing very disappointing results - for the Yn year (five year average), the Test sample results were 100%, 95% and 95%, respectively; with the Holdout sample results being 81.3%, 83.8% and 52.5%, respectively. The Yn-1 to Yn-3 models produced very good results for the Test sample but somewhat disappointing Holdout sample results. The best two Yn models namely, the Naïve and the CHAID models, were modified so as to enable a comparison with the notable, dichotomous De La Rey (1981) model. As such, three different approaches were adopted and in all cases, both the modified Naïve (100%, 81.3%, 100%) and the modified CHAID (100%, 85.9%, 98%) produced superior results to the De La Rey model (84.8%, 62.6%, 75.3%). For the second stage, a Financial Risk Analysis Model (FRAM) using ratios in the categories of Growth, Performance Analysis, Investment Analysis and Financial Status were used to provide underlying information or clues, independent of the first stage model, so as to enable the stakeholder to establish a more meaningful picture of the company. This would pave the way for the appropriate strategy and course of action to be followed, to take the company to the next level; whether it be taking the company out of a Distressed State (D) or further improving on its Healthy status (H). / Business Management / D. BL.

Le réchauffement climatique, la pollution de l'environnement et l'épuisement des énergies pétrolières ont attiré l'attention de l'humanité dans le monde entier. Les véhicules électriques hybrides à pile à combustible (FCHEV), utilisant l’hydrogène comme carburant et n’émettant aucune émission, sont considérés par les organismes publics et privés comme l’un des meilleurs moyens de résoudre ces problèmes. Cette thèse de doctorat considère un FCHEV avec trois sources d'énergie: pile à combustible, batterie et supercondensateur, ce qui complique l'élaboration d'une stratégie de gestion de l'énergie (EMS) pour répartir la puissance entre différentes sources d'alimentation. Parmi les méthodes de gestion de l'énergie de la littérature actuelle, la stratégie de minimisation de la consommation équivalente (ECMS) a été sélectionnée car elle permet une optimisation locale sans connaissance préalable des conditions de conduite et cela en donnant des résultats optimaux.En raison de la faible densité énergétique du supercondensateur, sa consommation équivalente d'hydrogène est négligée dans la plupart des références bibliographiques, ce qui va non seulement à l'encontre de l'objectif de minimiser la consommation totale d'hydrogène, mais accroît également la complexité du système EMS en raison du besoin d'un système EMS supplémentaire pour calculer la demande en puissance du supercondensateur. Ainsi, une stratégie ECMS à programmation quadratique séquentielle (SECMS) est proposée pour prendre en compte le coût énergétique des trois sources d’énergie dans la fonction objectif. Une stratégie de contrôle basée sur des règles (RBCS) et une stratégie hybride (HEOS) a été également conçues pour être comparée à SECMS. La dégradation des sources d'énergie représente un défi majeur pour la stabilité du système SECMS développé. Basé sur l'estimation en ligne de l'état de santé de la pile à combustible et de la batterie, le système ECMS adaptatif (AECMS) a été implémenté en ajustant le facteur équivalent et le taux de changement dynamique de la pile à combustible. Les résultats de la simulation montrent que l’AECMS peut assurer le maintien de la charge de la batterie et l’augmentation de la durabilité de la pile à combustible.Pour valider les algorithmes de gestion de l'énergie et les modèles numériques proposés, un banc d'essai expérimental a été construit autour de l'interface temps réel DSPACE. La comparaison des résultats de la simulation numérique et des résultats expérimentaux a montré que le système SECMS proposé fonctionne à un rendement maximal, que le supercondensateur fournit la puissance de pointe et que la batterie fonctionne comme un tampon d’énergie. Il a été prouvé que la négligence de la consommation d'hydrogène équivalente au supercondensateur dans l'ECMS conduit à un fonctionnement non optimal. Comparé à RBCS et HEOS, la SECMS a le moins d'hydrogène consommé et le courant de pile à combustible le plus stable. / Global warming, environment pollution and exhaustion of petroleum energies have risen their attention of the humanity over the world. Fuel cell hybrid electric vehicle (FCHEV) taking hydrogen as fuel and have zero emission, is thought by public and private organisms as one of the best ways to solve these problems. This PhD dissertation consider a FCHEV with three power sources: fuel cell, battery and supercapacitor, which increases the difficult to design an energy management strategy (EMS) to split the power between the different power sources.Among the EMS available in the current literature, the Equivalent consumption minimization strategy (ECMS) was selected because it allows a local optimization without rely on prior knowledge of driving condition while giving optimal results.Due to low energy density of supercapacitor, its equivalent hydrogen consumption is neglected in most bibliographic references, which not only counter to the aim of minimizing whole hydrogen consumption but also increase the complication of EMS due to the need of an additional EMS to calculate supercapacitor power demand. Thus, a sequential quadratic programming ECMS (SECMS) strategy is proposed to consider energy cost of all three power sources into the objective function. A rule based control strategy (RBCS) and hybrid strategy (HEOS) are also designed in order to to be compared with SECMS. Degradation of energy sources represents a major challenge for the stability of the developed SECMS system. So, based on online estimating state of heath of fuel cell and battery, an adaptive ECMS (AECMS) has been designed through adjusting the equivalent factor and dynamical change rate of fuel cell. The simulation results show that the AECMS can ensure the charge sustenance of battery and the increase of fuel cell durability.To validate the proposed energy management algorithms and the numerical models an exerimental test bench has been built around the real time interface DSPACE. The comparison of the simulation and experimental results showed that the proposed SECMS is operated at around maximum efficiency, supercapacitor supplies peak power, battery works as the energy buffer. It has been proved that the neglect of supercapacitor equivalent hydrogen consumption in ECMS leads to not optimal operation. Compared with RBCS and HEOS, SECMS has least hydrogen consumption and most stable fuel cell current.