This work presents a methodology capable of determining the energy demand of 5 bus lines in the city of Cuenca-Ecuador. The selected lines were chosen for being the ones with the highest number of passengers. The study was carried out by acquiring data from the OBD II port of the transport units through an open-source data logger device, which stores variables such as speed, acceleration, slope of the road, GPS location, etc. The acquired information was post-processed in MATLAB. By studying the analyzed variables, a model that allows identifying the relationship between the vehicle's specific power (VSP) and the energy consumption during the drives was determined. To calculate this value, the vehicle's mass, acceleration and its trajectory were taken into consideration. To avoid biases on the acquired information during the complete bus routes, statistical tools such as the analysis of variance and correlation were used to select schedules according to the city vehicular traffic. With use of machine learning techniques, the existing relationship between speed, acceleration, road slope and energy demand was evidenced, a factor that is directly related to emission of polluting gases from the units into the atmosphere. As a result of the investigation, a disparity was determined in the bus line routes design, with lines with maximum and minimum dispatch rates of 405 and 178, respectively. Several lines have extensive routes with consumption of 330.44 kW and slopes of 24.85%, for which a modification in the design of the routes could be suggested.
|Title of host publication||Communication, Smart Technologies and Innovation for Society - Proceedings of CITIS 2021|
|Editors||Álvaro Rocha, Paulo Carlos López-López, Juan Pablo Salgado-Guerrero|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||13|
|State||Published - 2022|
|Event||7th International Conference on Science, Technology and Innovation for Society, CITIS 2021 - Virtual, Online|
Duration: 26 May 2021 → 28 May 2021
|Name||Smart Innovation, Systems and Technologies|
|Conference||7th International Conference on Science, Technology and Innovation for Society, CITIS 2021|
|Period||26/05/21 → 28/05/21|
Bibliographical notePublisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
- Data logger
- Machine learning