| 000 | 02496nab a2200241 4500 | ||
|---|---|---|---|
| 005 | 20260520003100.0 | ||
| 008 | 260224s2012 xxu ing | ||
| 041 | _aInglés | ||
| 245 | 0 | 0 | _aIntelligent Energy Management for Plug-in Hybrid Electric Vehicles: The Role of ITS Infrastructure in Vehicle Electrification |
| 260 |
_a _b _cjul./ago. 2012 |
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| 270 | _a14/05/2013 ; 14/05/2013 | ||
| 300 | _a12 p. ; 575-587 | ||
| 520 | _aTraducción del resúmen del autor: The desire to reduce carbon emissions due to transportation sources has led over the past decade to the development of new propulsion technologies, focused on vehicle electrification (including hybrid, plug-in hybrid and battery electric vehicles). These propulsion technologies, along with advances in telecommunication and computing power, have the potential of making passenger and commercial vehicles more energy efficient and environment friendly. In particular, energy management algorithms are an integral part of plug-in vehicles and are very important for achieving the performance benefits. The optimal performance of energy management algorithms depends strongly on the ability to forecast energy demand from the vehicle. Information available about environment (temperature, humidity, wind, road grade, etc.) and traffic (traffic density, traffic lights, etc.), is very important in operating a vehicle at optimal efficiency. This article outlines some current technologies that can help achieving this optimum efficiency goal. In addition to information available from telematic and geographical information systems, knowledge of projected vehicle charging demand on the power grid is necessary to build an intelligent energy management controller for future plug-in hybrid and electric vehicles. The impact of charging millions of vehicles from the power grid could be significant, in the form of increased loading of power plants, transmission and distribution lines, emissions and economics (information are given and discussed for the US case). Therefore, this effect should be considered in an intelligent way by controlling/scheduling the charging through a communication based distributed control. | ||
| 581 | _a4 | ||
| 773 | 0 |
_tOil and Gas Science and Technology _g67 |
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| 942 | _cARTICULO | ||
| 100 | 1 |
_aMarano, V. _953154 |
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| 100 | 1 |
_aRizzoni, G. _953155 |
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| 100 | 1 |
_aTulpule, P. _953156 |
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| 100 | 1 |
_aGong, Q. _953157 |
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| 100 | 1 |
_aKhayyam, H. _953158 |
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| 999 |
_c187680 _d187680 |
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