: This paper addresses the problem of automatic motions for intelligent electric cars. We design a control hierarchical architecture composed of two levels : a reactive controller based on fuzzy logic and a local navigator based on direct model of mobile robot. The fuzzy controller works on a short

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on already existing business models that have proven themselves in other industries and they have been chosen in regards to their suitability to address important hindrances for a rapid plug-in car adoption like perceived risk, high purchase price and limited range. The four models are: All-electric car

Abstract. Environmental protection and energy issues have already become the two most prominent themes in the new century. Electric car becomes one of the ways to solve these two problems. Aiming at working out how to apply the brushless DC motor to the electric car, a control system was designed

In this paper, we show that the potential for endogenous technological change in alternative energy sources may alter the behaviour of resource-owning firms. When technological progress in an alternative energy source can occur through learning-by-doing, resource owners face competing incentives to extract rents from the resource and to prevent expansion of the new technology. We show that in such a context, it is not necessarily the case that scarcity-driven higher traditional energy prices over time will induce alternative energy supply as resources are exhausted. Rather, we show that as we increase the learning potential in the substitute technology, lower equilibrium energy prices prevail and there may be increased resource extraction and greenhouse gas emissions. We show that the effectiveness and the incidence of emissions reduction policies may be altered by increased potential for technological change. Our results suggest that treating finite resource rents as endogenous consequences of both technological progress and policy changes will be important for the accurate assessment of climate change policy.

In this paper, we show that the potential for endogenous technological change in alternative en-ergy sources may alter the behaviour of resource-owning firms. When technological progress in an alternative energy source can occur through learning-by-doing, resource owners face compet-ing incentives to extract rents from the resource and to prevent expansion of the new technology. We show that in such a context, it is not necessarily the case that scarcity-driven higher tradi-tional energy prices over time will induce alternative energy supply as resources are exhausted. Rather, we show that as we increase the learning potential in the substitute technology, lower equilibrium energy prices prevail and there may be increased resource extraction and greenhouse gas emissions. We show that the effectiveness and the incidence of emissions reduction policies may be altered by increased potential for technological change. Our results suggest that treat-ing finite resource rents as endogenous consequences of both technological progress and policy

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Abstract. Electric CAr Recharge Optimization Toolkit (e-CARROT) is an integrated system for modelling and optimization of Electric Vehicle recharge processes. It uses semantic technology to conceptualize, model, and optimize battery recharge processes occurring in smart grid. The e-CARROT tool

As concerns grow regarding the ever increasing use of fossil fuels, interest in vehicles powered by alternative energy sources continues to develop. This study investigates the feasibility of charging electric cars in Ontario, Canada with electricity generated from renewable sources. Two main

In the current climate debate, electric vehicles are widely considered to be the future of individual transport. The REV Project of the University of Western Australia has converted three regular petrol driven cars to electric vehicles. This thesis focusses on the user interface for one of those