Source: EURLEX
Language: es
Format: md

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| 10.2.2015 | ES | Diario Oficial de la Unión Europea | L 33/52 |

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DECISIÓN DE EJECUCIÓN (UE) 2015/206 DE LA COMISIÓN

de 9 de febrero de 2015

relativa a la aprobación de una iluminación exterior eficiente de Daimler AG que utiliza diodos emisores de luz como tecnología innovadora para la reducción de las emisiones de CO2 de los turismos de conformidad con el Reglamento (CE) no 443/2009 del Parlamento Europeo y del Consejo

(Texto pertinente a efectos del EEE)

LA COMISIÓN EUROPEA,

Visto el Tratado de Funcionamiento de la Unión Europea,

Visto el Reglamento (CE) no 443/2009 del Parlamento Europeo y del Consejo, de 23 de abril de 2009, por el que se establecen normas de comportamiento en materia de emisiones de los turismos nuevos como parte del enfoque integrado de la Comunidad para reducir las emisiones de CO2 de los vehículos ligeros [(1)](#ntr1-L_2015033ES.01005201-E0001), y, en particular, su artículo 12, apartado 4,

Considerando lo siguiente:

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| (1) | El 14 de noviembre de 2013, el fabricante Daimler AG («el solicitante») presentó una solicitud de aprobación de una iluminación exterior eficiente mediante diodos emisores de luz (LED) como paquete de tecnologías innovadoras. La integridad de la solicitud se evaluó de conformidad con el artículo 4 del Reglamento de Ejecución (UE) no 725/2011 de la Comisión [(2)](#ntr2-L_2015033ES.01005201-E0002). La Comisión observó la falta de cierta información pertinente en la solicitud original y pidió al solicitante que la completara. El solicitante facilitó dicha información el 14 de mayo de 2014. La solicitud se consideró completa, y el período para su evaluación por parte de la Comisión comenzó el día siguiente a la fecha de recepción oficial de la información completa, es decir, el 15 de mayo de 2014. |

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| (2) | La solicitud ha sido evaluada de conformidad con el artículo 12 del Reglamento (CE) no 443/2009, el Reglamento de Ejecución (UE) no 725/2011 y las orientaciones técnicas para la preparación de las solicitudes de aprobación de tecnologías innovadoras según el Reglamento (CE) no 443/2009 («las orientaciones técnicas») [(3)](#ntr3-L_2015033ES.01005201-E0003). |

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| (3) | La solicitud se refiere a una iluminación exterior eficiente mediante diodos emisores de luz en los faros de cruce, los faros de carretera, las luces de posición delanteras y la luz de placa de matrícula. Este paquete tecnológico es similar a las tecnologías innovadoras aprobadas como una ecoinnovación en las Decisiones de Ejecución 2013/128/UE [(4)](#ntr4-L_2015033ES.01005201-E0004) y 2014/128/UE [(5)](#ntr5-L_2015033ES.01005201-E0005) de la Comisión. Cabe señalar que la solicitud presentada por Daimler AG se basa, como la solicitud aprobada anteriormente mediante la Decisión de Ejecución 2014/128/UE, en el enfoque simplificado descrito en las orientaciones técnicas, mientras que la solicitud aprobada por la Decisión de Ejecución 2013/128/UE se basó en el enfoque global. |

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| (4) | La Comisión considera que la información presentada en la solicitud demuestra que se han cumplido las condiciones y los criterios mencionados en el artículo 12 del Reglamento (CE) no 443/2009, y en los artículos 2 y 4 del Reglamento de Ejecución (UE) no 725/2011. |

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| (5) | El solicitante ha demostrado que la utilización de los LED en los faros de cruce, los faros de carretera, las luces de posición delanteras y la luz de placa de matrícula no superó el 3 % de los turismos nuevos matriculados en el año de referencia (2009). Como prueba de ello, el solicitante se ha referido a las orientaciones técnicas, que proporcionan un resumen del informe sobre la iniciativa LIGHT Sight Safety de CLEPA. El solicitante ha utilizado funciones predefinidas y datos promediados en consonancia con el enfoque simplificado que se especifica en las orientaciones técnicas. |

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| (6) | De conformidad con el enfoque simplificado descrito en las orientaciones técnicas, el solicitante ha utilizado la iluminación halógena como tecnología de referencia para demostrar la capacidad de reducción de las emisiones de CO2 de la iluminación exterior eficiente mediante diodos emisores de luz en los faros de cruce, los faros de carretera, las luces de posición delanteras y la luz de placa de matrícula. |

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| (7) | El solicitante ha presentado una metodología para evaluar las reducciones de las emisiones de CO2 que incluye fórmulas que se ajustan a las descritas en las orientaciones técnicas para el enfoque simplificado por lo que se refiere a las funciones de iluminación. Dado que el solicitante ha presentado una solicitud respecto a un paquete de tecnologías innovadoras de iluminación exterior eficiente mediante LED, la Comisión considera adecuado modificar las fórmulas de cálculo de las reducciones de las emisiones de CO2 para reflejar el ahorro total de las emisiones de CO2 del paquete de iluminación. Así pues, la metodología especificada en el anexo de la decisión difiere en algunos elementos esenciales de la autorizada por la Decisión de Ejecución 2014/128/UE. La Comisión considera que con la metodología de ensayo se obtendrán resultados comprobables, repetibles y comparables, y que se podrán demostrar de forma realista las ventajas de la tecnología innovadora en cuanto a reducción de las emisiones de CO2 con fuerte significación estadística, de conformidad con lo dispuesto en el artículo 6 del Reglamento de Ejecución (UE) no 725/2011. |

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| (8) | Habida cuenta de ello, la Comisión considera que el solicitante ha demostrado satisfactoriamente que la reducción de emisiones lograda merced a la tecnología innovadora es de al menos 1 g de CO2/km. |

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| (9) | Dado que no se requiere la activación de las funciones de iluminación exterior para el ensayo de homologación de tipo sobre las emisiones de CO2 a que se refieren el Reglamento (CE) no 715/2007 del Parlamento Europeo y del Consejo [(6)](#ntr6-L_2015033ES.01005201-E0006) y el Reglamento (CE) no 692/2008 de la Comisión [(7)](#ntr7-L_2015033ES.01005201-E0007), la Comisión considera que las funciones de iluminación en cuestión no están cubiertas por el ciclo de ensayo estándar. |

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| (10) | La activación de las funciones de iluminación en cuestión es obligatoria para garantizar el funcionamiento seguro del vehículo y, por tanto, no depende de la elección del conductor. Sobre esa base, la Comisión considera que el fabricante debe ser considerado responsable de las reducciones de emisiones de CO2 debidas a la utilización de los LED. |

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| (11) | La Comisión constata que el informe de verificación ha sido elaborado por TÜV NORD Mobilität GmbH & Co. KG, organismo independiente y certificado, y que el informe corrobora las conclusiones expuestas en la solicitud. |

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| (12) | En este contexto, la Comisión considera que no deben plantearse objeciones a la aprobación de la tecnología innovadora en cuestión. |

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| (13) | Todo fabricante que desee beneficiarse de una reducción de sus emisiones específicas medias de CO2 para cumplir su objetivo de emisiones específicas mediante el descenso de las emisiones de CO2 derivado de la utilización de la tecnología innovadora aprobada mediante la presente Decisión debe hacer referencia, de conformidad con el artículo 11, apartado 1, del Reglamento de Ejecución (UE) no 725/2011, a la presente Decisión en su solicitud de certificado de homologación de tipo CE para los vehículos considerados. |

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| (14) | A fin de determinar el código general de las ecoinnovaciones que se deberá emplear en los documentos de homologación de tipo pertinentes de conformidad con los anexos I, VIII y IX de la Directiva 2007/46/CE del Parlamento Europeo y del Consejo [(8)](#ntr8-L_2015033ES.01005201-E0008), debe especificarse el código individual que se utilizará para la tecnología innovadora aprobada mediante la presente Decisión. |

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| (15) | El período para la evaluación de la tecnología innovadora a que se refiere el artículo 10, apartado 2, del Reglamento de Ejecución (UE) no 725/2011 está sujeto a expiración. Por tanto, procede que la Decisión entre en vigor lo antes posible. |

HA ADOPTADO LA PRESENTE DECISIÓN:

Artículo 1

1.   La iluminación exterior eficiente mediante diodos emisores de luz (LED), destinada a ser utilizada en vehículos de la categoría M1, queda aprobada como tecnología innovadora a efectos del artículo 12 del Reglamento (CE) no 443/2009.

2.   La reducción de las emisiones de CO2 derivada del uso de iluminación exterior eficiente mediante diodos emisores de luz mencionada en el apartado 1 se determinará utilizando la metodología establecida en el anexo.

3.   El código individual de ecoinnovación que deberá consignarse en la documentación de homologación de tipo correspondiente a la tecnología innovadora aprobada mediante la presente Decisión será el «10».

Artículo 2

La presente Decisión entrará en vigor el séptimo día siguiente al de su publicación en el Diario Oficial de la Unión Europea.

Hecho en Bruselas, el 9 de febrero de 2015.

Por la Comisión

El Presidente

Jean-Claude JUNCKER

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ANEXO

1.   Metodología de ensayo — Introducción

Para determinar las reducciones de emisiones de CO2 que pueden atribuirse a la utilización de la iluminación exterior eficiente mediante diodos emisores de luz (LED) en un vehículo de categoría M1, es necesario establecer lo siguiente:

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| a) | las condiciones de ensayo; |

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| b) | el procedimiento de ensayo; |

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| c) | las fórmulas para calcular el descenso de las emisiones de CO2; |

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| d) | las fórmulas para calcular la desviación típica; |

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| e) | la determinación del descenso de las emisiones de CO2 para la certificación por parte de las autoridades de homologación de tipo. |

2.   Condiciones de ensayo

Se aplicarán los requisitos del Reglamento (CEPE/ONU) no 112 [(1)](#ntr1-L_2015033ES.01005501-E0001), relativo a las prescripciones uniformes sobre la homologación de los faros de los vehículos de motor que emiten un haz de cruce o un haz de carretera asimétricos, o ambos, y están equipados con lámparas de incandescencia y/o módulos de diodos emisores de luz (LED). Para determinar el consumo de energía, debe hacerse referencia al punto 6.1.4. del Reglamento no 112, y a los puntos 3.2.1 y 3.2.2 del anexo 10 del Reglamento no 112.

3.   Procedimiento de ensayo

Las mediciones deben efectuarse como se muestra en la figura 1. Se utilizará el equipo siguiente:

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| — | Dos multímetros digitales, uno para medir la intensidad de la corriente continua y el otro para medir la tensión de la corriente continua. |

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| — | Una unidad de alimentación. |

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V9srvSHOU2bZqTVlGn//Z)

Figura 1 Disposición del ensayo

Lámpara LED

Unidad de alimentación

En total deben realizarse cinco mediciones de la intensidad con una tensión de 12,8 V para los faros de cruce, los faros de carretera y las luces de posición delanteras, y con una tensión de 10,7 V para la luz de placa de matrícula.

Las tensiones instaladas exactas y la intensidad medida deben registrarse al cuarto decimal.

4.   Fórmulas

Deben seguirse las siguientes etapas para determinar el descenso de las emisiones de CO2 y comprobar si se cumple el valor umbral de 1 g de CO2/km:

|  |  |  |
| --- | --- | --- |
| Etapa 1 | : | Calcular el descenso de las emisiones de potencia. |
| Etapa 2 | : | Calcular el descenso de las emisiones de CO2. |
| Etapa 3 | : | Calcular el error en el descenso de las emisiones de CO2. |
| Etapa 4 | : | Verificar el valor umbral. |

4.1.   Cálculo del ahorro de potencia

La potencia utilizada para cada una de las cinco mediciones debe calcularse multiplicando la tensión instalada por la intensidad de la corriente medida. Por tanto, cuando se utilice un motor de velocidad gradual o un regulador electrónico para el suministro de electricidad a las lámparas LED, debe excluirse de la medición la carga eléctrica de este componente. De este modo se obtendrán cinco valores. Cada valor ha de expresarse con cuatro decimales. A continuación se calculará el valor medio de la potencia utilizada, que es la suma de los cinco valores dividida por cinco.

El ahorro de potencia obtenido debe calcularse con la fórmula siguiente:

Fórmula (1)

ΔP = Pde referencia – Pecoinnovación

donde:

|  |  |  |
| --- | --- | --- |
| ΔP | : | ahorro de potencia, en W; |
| Pde referencia | : | potencia de la tecnología de referencia; |
| Pecoinnovación | : | valor medio de la potencia de la ecoinnovación utilizada, en W. |

Cuadro 1

Requisitos de potencia para diferentes tipos de iluminación de referencia

|  |  |
| --- | --- |
| Tipo de iluminación | Potencia eléctrica total  [W] |
| Faros de cruce | 137 |
| Faros de carretera | 150 |
| Luces de posición delanteras | 12 |
| Luz de placa de matrícula | 12 |

4.2.   Cálculo del descenso de las emisiones de CO2

El descenso total de las emisiones de CO2 derivado del paquete de iluminación debe calcularse mediante las fórmulas (2) y (3).

Respecto a los vehículos de gasolina:

Fórmula (2):

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)

Respecto a los vehículos diésel:

Fórmula (3):

![Formula](data:image/jpg;base64,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)

Esas fórmulas presentan el descenso total de las emisiones de CO2 del paquete de iluminación en g de CO2/km.

Los datos de entrada para las fórmulas (2) y (3) son los siguientes:

|  |  |  |
| --- | --- | --- |
| ΔPj | : | potencia eléctrica ahorrada en W para el tipo de iluminación j, que es el resultado de la etapa 1 |
| UFj | : | factor de utilización del tipo de iluminación j, indicado en el cuadro 2 |
| m | : | número de tipos de iluminación en el paquete de tecnologías innovadoras |
| v | : | velocidad media de conducción del NEDC, que es de 33,58 km/h |
| VPe – P | : | consumo de potencia efectiva de los vehículos de gasolina, que es de 0,264 l/kWh |
| VPe – D | : | consumo de potencia efectiva de los vehículos diésel, que es de 0,22 l/kWh |
| ηA | : | eficiencia del alternador, que es de 0,67 |
| CFP | : | factor de conversión para la gasolina, que es de 2 330 g de CO2/l |
| CFD | : | factor de conversión para el gasóleo, que es de 2 640 g de CO2/l |

Cuadro 2

Factor de utilización para diferentes tipos de iluminación

|  |  |
| --- | --- |
| Tipo de iluminación | Factor de utilización (FU) |
| Faros de cruce | 0,33 |
| Faros de carretera | 0,03 |
| Luces de posición delanteras | 0,36 |
| Luces de placa de matrícula | 0,36 |

4.3.   Cálculo del error estadístico en el descenso de las emisiones de CO2

El error estadístico en el descenso de las emisiones de CO2 debe determinarse en dos etapas. En la primera etapa, el valor de error de la potencia se determinará como una desviación típica equivalente a un intervalo de confianza del 68 %.

Esto se hará mediante la fórmula (4).

Fórmula (4):

![Formula](data:image/jpg;base64,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)

donde:

|  |  |  |
| --- | --- | --- |
| Formula | : | desviación típica de la media aritmética [W] |
| xi | : | valor de medición [W] |
| Formula | : | media aritmética [W] |
| n | : | número de mediciones, que es 5 |

Para calcular el error en el descenso de las emisiones de CO2 respecto a los vehículos de gasolina y diésel, debe aplicarse la ley de propagación, expresada en la fórmula (5).

Fórmula (5):

![Image 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)

donde:

|  |  |  |
| --- | --- | --- |
| Formula | : | error medio total del descenso de las emisiones de CO2 [gCO2/km] |
| Image 3 | : | sensibilidad del descenso de las emisiones de CO2 calculado en relación con el tipo de iluminación Pj |
| σPj | : | error del tipo de iluminación Pj [W] |
| m | : | número de tipos de iluminación en el paquete de tecnologías innovadoras |

La sustitución de la fórmula (2) en la fórmula (5) conduce a la fórmula (6) para calcular el error en el descenso de las emisiones de CO2, respecto a los vehículos de gasolina.

Fórmula (6):

![Formula](data:image/jpg;base64,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)

La sustitución de la fórmula (3) en la fórmula (5) conduce a la fórmula (7) para calcular el error en el descenso de las emisiones de CO2, respecto a los vehículos diésel.

Fórmula (7):

![Formula](data:image/jpg;base64,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)

4.4.   Verificación del valor umbral

Para demostrar que el umbral de 1,0 g de CO2/km se supera de manera estadísticamente significativa, debe utilizarse la fórmula (8) siguiente.

Fórmula (8):

![Formula](data:image/jpg;base64,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)

donde:

|  |  |  |
| --- | --- | --- |
| MT | : | umbral mínimo [gCO2/km] |
| CCO2 | : | descenso total de las emisiones de CO2 (g de CO2/km), que debe expresarse con cuatro decimales |
| Formula | : | error medio total del descenso de las emisiones de CO2 [g de CO2/km], que debe expresarse con cuatro decimales |

En caso de que el descenso total de las emisiones de CO2 del paquete de tecnologías innovadoras, como consecuencia del cálculo según la fórmula (8), se sitúe por debajo del umbral previsto en el artículo 9, apartado 1, del Reglamento de Ejecución (UE) no 725/2011, será de aplicación el artículo 11, apartado 2, párrafo segundo, de dicho Reglamento.

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[(1)](#ntc1-L_2015033ES.01005501-E0001)  E/ECE/324/Rev.2/Add.111/Rev.3—E/ECE/TRANS/505/Rev.2/Add.111/Rev.3, 9 de enero de 2013.

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