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    Design and analysis of kinetic energy recovery system for automobiles: Case study for commuters in Edinburgh
    (Amer Inst Physics, 2011) Walsh, John; Muneer, Tariq; Çelik, Ali Naci
    Transport and its energetic and environmental impacts affect our daily lives. The transport sector is the backbone of the United Kingdom's economy with 2.3 million people being employed in this sector. With a high dependency on transport for passengers and freight and with the knowledge that oil reserves are rapidly decreasing a solution has to be identified for conserving fuel. Passenger vehicles account for 61% of the transport fuel consumed in the U. K. and should be seen as a key area to tackle. Despite the introduction and development of electric powered cars, the widespread infrastructure that is required is not in place and has attributed to their slow uptake, as well as the fact that the electric car's performance is not yet comparable with the conventional internal combustion engine. The benefits of the introduction of kinetic energy recovery systems to be used in conjunction with internal combustion engines and designed such that the system could easily be fitted into future passenger vehicles are examined. In this article, a review of automobile kinetic energy recovery system is presented. It has been argued that the ultracapacitor technology offers a sustainable solution. An optimum design for the urban driving cycle experienced in the city of Edinburgh has been introduced. The potential for fuel savings is also presented. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3549152]
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    Neural network based method for conversion of solar radiation data
    (Pergamon-Elsevier Science Ltd, 2013) Çelik, Ali Naci; Muneer, Tariq
    The receiving ends of the solar energy conversion systems that generate heat or electricity from radiation is usually tilted at an optimum angle to increase the solar incident on the surface. Solar irradiation data measured on horizontal surfaces is readily available for many locations where such solar energy conversion systems are installed. Various equations have been developed to convert solar irradiation data measured on horizontal surface to that on tilted one. These equations constitute the conventional approach. In this article, an alternative approach, generalized regression type of neural network, is used to predict the solar irradiation on tilted surfaces, using the minimum number of variables involved in the physical process, namely the global solar irradiation on horizontal surface, declination and hour angles. Artificial neural networks have been successfully used in recent years for optimization, prediction and modeling in energy systems as alternative to conventional modeling approaches. To show the merit of the presently developed neural network, the solar irradiation data predicted from the novel model was compared to that from the conventional approach (isotropic and anisotropic models), with strict reference to the irradiation data measured in the same location. The present neural network model was found to provide closer solar irradiation values to the measured than the conventional approach, with a mean absolute error value of 14.9 Wh/m(2). The other statistical values of coefficient of determination and relative mean absolute error also indicate the advantage of the neural network approach over the conventional one. In terms of the coefficient of determination, the neural network model results in a value of 0.987 whereas the isotropic and anisotropic approaches result in values of 0.959 and 0.966, respectively. On the other hand, the isotropic and anisotropic approaches give relative mean absolute error values of 11.4% and 11.5%, respectively, while that of the neural network model is 9.1%. (C) 2012 Elsevier Ltd. All rights reserved.
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    A sustainable transport solution for a Slovenia town
    (Oxford Univ Press, 2015) Knez, Matjaz; Çelik, Ali Naci; Muneer, Tariq
    Authorities in Slovenia and other EU member states are confronted with problems of city transportation. Fossil-fuel-based transport poses two chief problems-local and global pollution, and dwindling supplies and ever-increasing costs. An elegant solution is to gradually replace the present automobile fleet with electric vehicles (EVs). This article explores the economics and practical viability of the provision of solar electricity for the charging of EVs by installation of economical available Photovoltaic modules. A steep decline in the module, inverter and installation costs is reported herein. Present estimates indicate that for the prevailing solar climate of Celje-a medium-sized Slovenian town-the cost would be only 2 euros and 11 cents per kWh of generated solar electricity.