published_or_final_version / Environmental Management / Master / Master of Science in Environmental Management

The purpose of this study was to determine consumers' attitudes toward and perceptions of global warming and hybrid cars and examine the car purchasing behavior in Singapore. The benefits of the study will provide marketers with insight of consumers' demand for cars in Singapore. Findings will help automakers develop more effective, consumer-oriented advertising plans for cars in Asia as Singapore consists of diverse Asian ethnic backgrounds- Chinese, Indian, and Malaysain.

De nouvelles architectures de traction (hybride, électrique) entrent en concurrence avec les motorisations thermiques conventionnelles. Des batteries Lithium-ion équipent ces véhicules innovants. La durabilité de ces batteries constitue un enjeu majeur mais dépend de nombreux paramètres environnementaux externes. Les outils de prédiction de durée de vie actuellement utilisés sont souvent trop simplificateurs dans leur approche. L’objet de ces travaux consiste à caractériser les conditions d’usage de ces batteries (température, tension, courant, SOC et DOD) afin d’étudier avec précision la durée de vie que l’on peut en attendre en fonction de l’application visée. Différents types de véhicules électrifiés (vélos à assistance électrique, voitures électriques, voitures hybrides, et trolleybus) ont été instrumentés afin de documenter les conditions d’usage réel des batteries. De larges volumes de données ont été recueillis puis analysés au moyen d’une méthode innovante qui s’appuie sur la classification d’impulsions de courant par l’algorithme des K-means et la génération de cycles synthétiques par modélisation par chaine de Markov. Les cycles synthétiques ainsi obtenus présentent des caractéristiques très proches de l’échantillon complet de données récoltées et permettent donc de représenter fidèlement l’usage réel. Utilisés lors de campagnes de vieillissement de batteries, ils sont susceptibles de permettre l’obtention d’une juste prédiction de la durée de vie des batteries pour l’application considérée. Plusieurs résultats expérimentaux sont présentés afin d’étayer la pertinence de cette approche / Lithium-ion batteries are being used as energy storage systems in recent electric and hybrid electric vehicles coming to market. Current cycle-life estimation techniques show evidence of discrepancy between laboratory results and real-world results. This work is aimed at characterizing actual battery usage in electrified transportation applications. Factors such as temperature, State Of Charge, Depth Of Discharge, current and voltage have to be carefully considered for accurate cycle-life prediction within a given application. Five electrified vehicles have been studied (two electric bicycles, one light EV, one mainstream HEV and one Heavy-Duty trolleybus). These vehicles have been equipped with sensors and data-logger and then test-driven on open roads under real-world conditions. Large amounts of data have been stored and later processed through an innovative method for analysis of actual usage. This method relies on data mining based on K-means clustering and synthetic duty cycle generation based on Markov chain modeling. Resulting synthetic cycles exhibit features similar to those observed on the large original datasets. This enables accurate prediction of cycle-life through realistic ageing trials of Lithium-ion batteries. Several experimental results are presented in order to assess the fitness of this method

Indiana University-Purdue University Indianapolis (IUPUI) / Lithium-ion battery is one kind of rechargeable battery, and also renewable, sustainable and portable. With the merits of high density, slow loss of charge when spare and no memory effect, lithium-ion battery is widely used in portable electronics and hybrid vehicles. Apart from its advantages, safety is a major concern for Lithium-ion batteries due to devastating incidents with laptop and cell phone batteries. Overcharge and over-discharge are two of the most common electrical abuses a lithium-ion battery suffers. In this thesis, a fuzzy-rule-based system is proposed to detect the over-charge and over-discharge failure in early time. The preliminary results for the failure signatures of overcharged and over-discharged lithium-ion are listed based on the experimental results under both room temperature and high temperature. A fuzzy-rule-based model utilizing these failure signatures is developed and validated. For over-charge case, the abnormal increase of the surface temperature and decrease of the voltage are captured. While for over discharge case, unusual temperature increase during overcharge phases and abnormal current decrease during overcharge phases are obtained. The inference engine for fuzzy-rule-based system is designed based on these failure signatures. An early warning signal will be given by this algorithm before the failure occurs. This failure detection and early warning system is verified to be effective through experimental validation. In the validation test, the proposed methods are successfully implemented in a real-time system for failure detection and early warning. The result of validation is compatible with the design expectation. Finally an accurate failure detection and early warning system is built and tested successfully.

<p dir="ltr">Electric roadways (ERs) represent a new paradigm for electrified transportation that is</p><p dir="ltr">enabled by the emerging dynamic (in-motion) wireless power transfer technology. Large-scale</p><p dir="ltr">integration of DWPT systems into power grids can pose a problem due to its high-power</p><p dir="ltr">requirements, significant number of power electronic converters and spatial concentration.</p><p dir="ltr">Despite their potential magnitude, the operational impacts of DWPT on the power grid have</p><p dir="ltr">not been fully studied in the literature. This dissertation contributes to our understanding</p><p dir="ltr">of how ERs could be successfully integrated with the electric power system at a diverse range</p><p dir="ltr">of spatial and temporal levels.</p><p dir="ltr">On a macroscopic level, a framework for assessing the financial viability of ERs is proposed.</p><p dir="ltr">Annual ER load estimations from traffic flow models of electric vehicles are used to</p><p dir="ltr">generate energy forecasts and carry out a financial evaluation. These models are also used to</p><p dir="ltr">plan distribution system capacity expansion. On a mesoscopic level, a data-driven design of</p><p dir="ltr">ERs and their interconnection with the distribution grid is presented. A data-based stochastic</p><p dir="ltr">traffic flow model is developed and used for designing the interconnection of the DWPT</p><p dir="ltr">system with the distribution grid ensuring adequate power transmission to high penetration</p><p dir="ltr">levels of heavy-duty trucks. The model is also used for conducting a series of quasi-steady</p><p dir="ltr">state studies on the power distribution system. On a microscopic level, a methodology for</p><p dir="ltr">modeling ER systems for time-domain simulations is proposed. Dynamic component models</p><p dir="ltr">are developed for the DWPT system. Power electronics are modeled using average-value</p><p dir="ltr">representations and integrated with models of the distribution grid. The models are used for</p><p dir="ltr">time-domain system simulations, transient analysis, fault analysis and power quality studies.</p><p dir="ltr">Theoretical analysis as well as numerical case studies and simulations of the proposed</p><p dir="ltr">methodologies are presented.</p>

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This doctoral dissertation examines the mode and efficacy of environmental and climate policy in China’s automotive sector. The ascent of China’s automobile market to the largest worldwide has detrimental effects on the country’s energy security situation, worsens environmental pollution, and increases greenhouse gas emissions. Environmental and climate policy measures to ameliorate these repercussions are the most apt tools available to the Chinese government. The objective of this dissertation is to identify the dominant mode of environmental and climate policies in China’s automotive industry and to assess the efficacy of select policy instruments. It does so by asking whether a uniform national approach to policy instrument adoption can be discerned that reflects China’s institutional and administrative history or whether modal exceptions exist. Secondly, if modal differences exist, to what extent do different instruments confirm the current understanding of the advantages and pitfalls of individual policy instrument types? And finally, how do Chinese instruments compare to those in other ambits in terms of policy mode and instrument efficacy? The literature on policy instruments holds that, due to their alleged efficiency advantages, incentive-based instruments dominate the political agenda of industrialised countries and international organisations (environmental consensus). This favouring of flexible instruments in academic and political circles contrasts with an evident lack of incentive-based instruments in practice and an observed lack of efficiency of some of those instruments actually implemented. Moreover, the policy mode adopted in developing countries and emerging markets has not yet received sufficient academic attention despite significant differences in institutional design, enforcement capacities, resources, and development paths that may imply reason for modal deviation. Applying a blend of qualitative and quantitative social sciences research methods, I add the case of China to the comparative literature and show that command-and-control regulation indeed forms the backbone of environmental and climate policy in China’s automotive industry. At the same time, modal differences exist between national regulation and local/ municipal incentive-based policy as well as in the electric vehicle sector, which shows a trend towards more incentive-based instruments and flexibility mechanisms in conventional regulation. Compared to other ambits, China has established a relatively flexible policy regime, at least for the case of vehicle efficiency standards. For the time being, incentive-based instruments remain comparatively ineffective and flexibility mechanisms in conventional regulation have an erosive effect on instrument stringency.

Large penetration of distributed generation from variable renewable energy sources, increased consumption flexibility on the demand side and the electrification of transportation pose great challenges to existing and future electric distribution networks. This thesis studies the roles of several actors involved in electric distribution systems through electricity consumption data analysis and simulation models. Results show that real-time electricity pricing adoption in the residential sector offers economic benefits for end consumers. This occurs even without the adoption of demand-side management strategies, while real-time pricing also brings new opportunities for increasing consumption flexibility. This flexibility will play a critical role in the electrification of transportation, where scheduled charging will be required to allow large penetration of EVs without compromising the network's reliability and to minimize upgrades on the existing grid. All these issues add significant complexity to the existing infrastructure and conventional passive components are no longer sufficient to guarantee safe and reliable network operation. Active distribution networks are therefore required, and consequently robust and flexible modelling and simulation computational tools are needed for their optimal design and control. The modelling approach presented in this thesis offers a viable solution by using an equation-based object-oriented language that allows developing open source network component models that can be shared and used unambiguously across different simulation environments.

Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2009. / ENGLISH ABSTRACT: With the current worldwide energy problems electric vehicles are set to replace conventional combustion engine vehicles. Electric vehicles with gearless in-wheel mounted brushless permanent magnet motors provide a more flexible and efficient means of vehicle propulsion but the electric motors, particularly the non-overlap stator winding type have not been fully researched. This study focuses on the selection and design of suitable in-wheel hub drive machine. Several machine topologies are evaluated and the single-sided axial flux machine is chosen. The average vehicle requirements are determined and design optimisations are carried with the aid of finite element analysis and an optimisation algorithm. A comparison of torque quality between single-layer and double-layer machines is carried out and it is found that double-layer machines have the least torque ripple and single-layer machines with un-equal teeth the best torque per ripple characteristics. A 16 kW, 30-pole 27-slot prototype machine optimised for power density is built, and it is found fitting for the application meeting the design requirements. The prototype machine is extensively tested and good agreement is found between finite element and measured results. The well known axial flux attraction forces are encountered in the prototype machine and they are overcome by suitable bearing selection and mechanical design. It is found that theoretical and measured cogging torques are inconsistent, the reason for this is that practical machines are not absolutely ideal due to material and manufacturing tolerances. Excessive rotor losses are found in the prototype machine and appropriate methods for their reduction are presented. This work does not aim to find the best in-wheel hub drive solution, but instead looks to uncover some of the technical available solutions. / AFRIKAANSE OPSOMMING: Met die huidige wêreldwye energie probleme, is elektriese voertuie bestem om konvensionele binnebrandenjin voertuie te vervang. Elektriese voertuie met ratlose binnewiel-geleë borsellose permanente magneet motors, voorsien „n meer aanpasbare en effektiewe metode van voertuig aandrywing, maar die elektriese motors, veral die oorvleulende stator winding tipe is nog nie ten volle nagevors nie. Hierdie studie fokus op die keuse en ontwerp van „n binnewiel aandryf masjien. Verskeie masjien uitlegte word geëvalueer en „n enkelkant aksiaalvloed masjien is gekies. Die gemiddelde voertuig behoeftes word bepaal en ontwerp optimalisering word uitgevoer met behulp van eindige element analise en „n optimaliserings algoritme. Enkellaag en dubbellaag masjiene se draaimoment kwaliteit word vergelyk. Die bevinding is dat dubbellaag masjiene die laagste draaimoment rimpel toon terwyl die enkellaag masjiene, met oneweredige tande, die beste draaimoment per rimpel karakteristieke toon. „n 16 kW, 30 pool, 27 gleuf prototipe masjien, wat vir drywingsdigtheid ge-optimaliseer is, is gebou en is geskik vir die toepassing en die vereistes. Die prototipe masjien is getoets en goeie vergelykings word getref tussen die eindige element analise en die gemete resultate. Die alom bekende aksiaal vloed aantrekkings kragte word in die prototipe masjien gesien en word oorkom deur die regte rollaer keuse en meganiese ontwerp. Nog „n bevinding is dat die teoretiese en gemete waardes vir die vertandings draaimoment nie ooreenstem nie. Die rede hiervoor is dat die praktiese masjien nie ideaal is in terme van materiaal en vervaardigings toleransies nie. Groot rotor verliese in die prototipe masjien is gevind en goeie metodes vir die minimering daarvan word voorgestel. Hierdie werk is nie „n soektog na die beste binnewiel aandrywings oplossing nie, maar mik eerder om sommige van die tegniese beskikbare oplossings te onthul.

In today’s world of volatile fuel prices and climate concerns, there is little study on the relation between vehicle ownership patterns and attitudes toward potential policies and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s household-fleet evolution. Results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are vehicle purchase price, type/class, and fuel economy (with 30%, 21% and 19% of respondents placing these in their top three). Most (56%) respondents also indicated that they would seriously consider purchasing a Plug-In Hybrid Electric Vehicle (PHEV) if it were to cost $6,000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings. 25-year simulations suggest that 19% of Austin’s vehicle fleet could be comprised of Hybrid Electric Vehicles (HEVs) and PHEVs under adoption of a feebate policy (along with PHEV availability in Year 1 of the simulation, and current gas prices throughout). Under all scenarios vehicle usage levels (in total vehicle miles traveled [VMT]) are predicted to increase overall, along with average vehicle ownership levels (per household, and per capita); and a feebate policy is predicted to raise total regional VMT slightly (just 4.43 percent, by simulation year 25), relative to the trend scenario, while reducing CO2 emissions only slightly (by 3.8 percent, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 17% and CO2 emissions by 22% (relative to trend). Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. And HEVs, PHEVs and Smart Cars are estimated to represent a major share of the fleet’s VMT (25%) by year 25 under the feebate scenario. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet), yet feebate-policy receipts exceed rebates in each simulation year. A 15% reduction in the usage levels of SUVs, CUVs and minivans is observed in the $5/gallon scenario (relative to trend). Mean use levels per vehicle of HEVs and PHEVs are simulated to have a variation of 753 and 495 across scenarios. In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have even more significant effects on energy dependence and greenhouse gas emissions. / text