Data Driven Energy Economy Prediction of Electric Buses Using Machine Learning
Author:
G N PoojaORCID, Jakaraddi Hanamant R.ORCID, Diwan Aditya UORCID
Publisher
QTanalytics India
Reference27 articles.
1. Aljohani, T. M., Ebrahim, A., & Mohammed, O. (2021). Real-Time metadata-driven rout ing optimization for electric vehicle energy consumption minimization using deep reinforcement learning and Markov chain model. Electric Power Systems Research, 192. https://doi.org/10.1016/j.epsr.2020.106962 2. Asamer, J., Graser, A., Heilmann, B., & Ruthmair, M. (2016). Sensitivity analysis for energy demand estimation of electric vehicles. Transportation Research Part D: Transport and Environment, 46, 182-199. https://doi.org/10.1016/j.trd.2016.03.017 3. Chen, Y., Wu, G., Sun, R., Dubey, A., Laszka, A., & Pugliese, P. (2021). A Review and Outlook on Energy Consumption Estimation Models for Electric Vehicles. SAE International Journal of Sustainable Transportation, Energy, Environment, Policy, 2(1). https://doi.org/10.4271/13-02-01-0005 4. De Cauwer, C., Van Mierlo, J., & Coosemans, T. (2015). Energy consumption prediction for electric vehicles based on real-world data. Energies, 8(8), 8573-8593. https://doi.org/10.3390/en8088573 5. Ericsson, E. (2001). Independent driving pattern factors and their influence on fuel-use and exhaust emission factors. Transportation Research Part D: Transport and Environment, 6(5), 325-345. https://doi.org/10.1016/S1361-9209(01)00003-7
|
|