Micromobility and smart cities: efficiency, energy consumption and range analysis for electric vehicles
Climate change and smart cities are topics where a large number of resources are being invested to avoid it and advance its development respectively. This paper presents a calculation procedure of the car efficiency, energy consumption and range whose efficiency has already been tested for hybrid ve...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/381206 |
| Acceso en línea: | https://hdl.handle.net/2117/381206 https://dx.doi.org/10.1051/rees/2021052 |
| Access Level: | acceso abierto |
| Palabra clave: | City planning Electric vehicles Sustainable development Consumption Efficiency Electric vehicle Energy Micromobility Quadricycle Range Smart city Vehicle category Urbanisme Vehicles elèctrics Desenvolupament sostenible Àrees temàtiques de la UPC::Desenvolupament humà i sostenible |
| Sumario: | Climate change and smart cities are topics where a large number of resources are being invested to avoid it and advance its development respectively. This paper presents a calculation procedure of the car efficiency, energy consumption and range whose efficiency has already been tested for hybrid vehicles (including plug-in) and fuel cell vehicles, as well as pure electric vehicles of category M1. This method has been adapted for quadricycles of category L6e and L7e in order to be able to use it to accelerate the design of this type of vehicles and contribute to its introduction in Smart Cities. The reliability of the system has been verified with commercially available vehicles and prototypes taking into account their technical specifications: electric motor (e.g., permanent magnet motor), technology of energy storage system (e.g., lithium-ion battery), weight and geometry of the car for all types of drive cycles. According to the literature review, there is currently no standardized operating system or hardware abstraction layer for such methodology/application in the automotive sector. This flexible method can be easily extended for different technologies of batteries and electric motors, different standard or customized drive cycles, etc. Besides, it has high reliability for vehicles of category L since in no case does the error reach 5 % and the average value is 2.5 % when real data from vehicle manufacturers and outcomes are compared. Thus, results show the consistency of the system. |
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