Ir directamente a la navegación principal Ir directamente a la búsqueda Ir directamente al contenido principal

Evaluation Framework of Next Generation Electric Trucks

  • Dimitris Margaritis*
  • , Lukasz Zymelka
  • , Hans Michael Koegeler
  • , Leo Xanakis
  • , Sophie Naylor
  • , Victor Lejona
  • , Jorden Vander Hoogt
  • , Daanvan Rooij
  • , Iban Vicente Makazaga
  • , Dai Duong Tran
  • *Autor correspondiente de este trabajo
  • Center for Research and Technology - Hellas
  • Netherlands Organisation for Applied Scientific Research
  • AVL List GmbH
  • CENEX UK
  • CENEX NL
  • VUB

Producción científica: Capítulo del libro/informe/acta de congresoCapítulorevisión exhaustiva

Resumen

To measure the success of a research and development project and assess its impact, an evaluation methodology has to be established. The proposed methodology in the NextETRUCK project follows best practices in validation and draws on insights from previous support projects such as CONVERGE and FESTA. It outlines a set of research hypotheses and associated goals for different innovation aspects of the project, forming the basis for evaluation. Key elements of this evaluation plan include defining Key Performance Indicators (KPIs). A total of 28 KPIs have been identified, covering areas such as vehicle and charging performance, digital tools, driver/fleet operator experiences, and market/total cost of ownership considerations. These KPIs can be measured during the demonstration and digital twin operations, using both quantitative and qualitative measures. Objective data, subjective evaluations, and inputs such as vehicle data, questionnaires, and driver interviews can all contribute to the assessment. The evaluation plan takes a structured approach, detailing each KPI’s description, assessment methods, parameters, and necessary information to address potential risks and challenges during the evaluation phase.

Idioma originalInglés
Título de la publicación alojadaLecture Notes in Intelligent Transportation and Infrastructure
EditorialSpringer Nature
Páginas666-682
Número de páginas17
DOI
EstadoPublicada - 2025

Serie de la publicación

NombreLecture Notes in Intelligent Transportation and Infrastructure
VolumenPart F154
ISSN (versión impresa)2523-3440
ISSN (versión digital)2523-3459

Huella

Profundice en los temas de investigación de 'Evaluation Framework of Next Generation Electric Trucks'. En conjunto forman una huella única.

Citar esto