This content is not included in your SAE MOBILUS subscription, or you are not logged in.
Environmental Traffic Modeling and Simulation SIL Toolset for Electrified Vehicles
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 06, 2021 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Event: SAE WCX Digital Summit
With the enhancements in vehicle electrification and autonomous vehicles, Traffic systems are also being improved at an accelerated rate to aid the development of improving fuel economy standards. For this to be possible, it is essential that traffic can be accurately modeled and predicted. The existing toolsets are proprietary and expensive and traffic modeling is not a trivial task due to its dependence on various factors such as place, time, and weather. To address these issues, an entirely open-source Software-In-Loop (SIL) fleet-focused traffic modeling toolset has been developed with the ability to take environmental factors with powertrain-in-the-loop into account leveraging Simulation of Urban Mobility (SUMO) and python.
The proposed SIL toolset encompasses the creation of a microscopic traffic distribution which accounts for the usual traffic trends of a typical day. Parameters such as the number of vehicles entering the network and the speed of all the vehicles at a time of a day can be controlled by tunable weather conditions, which is obtained using weather APIs or datafiles. Given a network, origin and destination roads can be defined to create the routes based on shortest distance using default algorithms (like DUAROUTER) in SUMO on a pre-defined real network from Open Street Map or similar mapping standard. In this current study, the ego vehicle has been called into the traffic system after every hour, and information like battery charge, vehicle speed, and time of its trip are logged after every second at different traffic conditions. This developed framework can be used to test electric vehicles or fleets in a typical traffic scenario (which is determined by the weather conditions) and the effects of the traffic on the ego vehicle’s properties like the state of charge of the battery can be studied and modeled. This work can be extended to CAVs by using communication tools like Veins and OMNET++.
CitationPadisala, S. and Yurkovich, B., "Environmental Traffic Modeling and Simulation SIL Toolset for Electrified Vehicles," SAE Technical Paper 2021-01-0176, 2021, https://doi.org/10.4271/2021-01-0176.
Data Sets - Support Documents
|Unnamed Dataset 1|
|Unnamed Dataset 2|
|Unnamed Dataset 3|
- Ersal , T. , Kolmanovsky , I. , Masoud , N. , Ozay , N. et al. Connected and Automated Road Vehicles: State of the Art and Future Challenges International Journal of Vehicle Mechanics and Mobility 58 5 672 704 2020 10.1080/00423114.2020.1741652
- Gong , X. , Guo , Y. , Feng , Y. , Sun , J. et al. Evaluation of the Energy Efficiency in a Mixed Traffic with Automated Vehicles and Human Controlled Vehicles 21st International Conference on Intelligent Transportation Systems (ITSC) Maui 2018 1981 1986 10.1109/ITSC.2018.8569705
- Qu , X. , Yu , Y. , Zhu , M. , Lin , C. et al. Jointly Dampening Traffic Oscillations and Improving Energy Consumption with Electric, Connected and Automated Vehicles: A Reinforcement Learning Based Approach Applied Energy 2020 https://doi.org/10.1016/j.apenergy.2019.114030
- Lin , Q. , Li , S. , Du , X. , Zhang , X. et al. Minimize the Fuel Consumption of Connected Vehicles Between Two Red-Signalized Intersections in Urban Traffic IEEE Transactions on Vehicular Technology 67 10 9060 9072 2018 10.1109/TVT.2018.2864616
- Alvarez , M. , Chu , X. , Rodriguez , M.A. , Al-Mamun , A. et al. Reducing Road Vehicle Fuel Consumption by Exploiting Connectivity and Automation: A Literature Survey 14th International Symposium on Advanced Vehicle Control 2018 arXiv:2011.14805
- Lopez , P.A. , Behrisch , M. , Bieker-Walz , L. , Erdmann , J. et al. Microscopic Traffic Simulation Using SUMO 21st International Conference on Intelligent Transportation Systems (ITSC) Maui 2018 10.1109/ITSC.2018.8569938
- Haklay , M. , and Weber , P. OpenStreetMap: User-Generated Street Maps IEEE Pervasive Computing 7 4 12 18 2008 10.1109/MPRV.2008.80
- Bell , M.G.H. The Estimation of an Origin-Destination Matrix from Traffic Counts Transportation Science 17 2 123 232 1983 10.1287/trsc.17.2.198
- Sciarretta , A. and Vahidi , A. Energy Saving Potentials of CAVs Energy-Efficient Driving of Road Vehicles Lecture Notes in Intelligent Transportation and Infrastructure 2019 1 31 https://doi.org/10.1007/978-3-030-24127-8_1
- Shao , H. , Lam , W.H.K. , Sumalee , A. , Chen , A. et al. Estimation of Mean and Covariance of Peak Hour Origin-Destination Demands from Day-to-Day Traffic Counts Transportation Research Part B: Methodological 68 52 75 2014 https://doi.org/10.1016/j.trb.2014.06.002
- n.d. https://www.noaa.gov/weather
- Mahmassani , H.S. , Dong , J. , Kim , J. et al. 2009 https://rosap.ntl.bts.gov/view/dot/3990/dot_3990_DS1.pdf
- McDonough , M. , Shamsi , P. , and Fahimi , B. Application of Multi-port Power Electronic Interface: Plug-In Electric Vehicle Charging Platform IEEE International Symposium on Industrial Electronics 2012 975 980 10.1109/ISIE.2012.6237221
- n.d. https://sumo.dlr.de/docs/Car-Following-Models.html
- Brodsky , P. , Canova , M. , Kim , J. , Ramesh , P. et al. Calibration of Electrochemical Models for Li-Ion Battery Cells Using Three-Electrode Testing SAE Technical Paper 2020-01-1184 2020 https://doi.org/10.4271/2020-01-1184
- Freudiger , D. , D’Arpino , M. , and Canova , M. A Generalized Equivalent Circuit Model for Design Exploration of Li-Ion Battery Packs Using Data Analytics IFAC-Papers OnLine 52 5 568 273 2019 10.1016/j.ifacol.2019.09.090
- Yurkovich , B.J. , and Guezennec , Y. Dynamic Electrothermal Battery Pack Modelling and Simulation of Pack Imbalance International Journal of Powertrains 182 231 2012 10.1504/IJPT.2013.054156
- Sulzer , V. , Marquis , S.G. , Timms , R. , Robinson , M. et al. Python Battery Mathematical Modelling (PyBaMM) ECSarXiv 2020 10.1149/osf.io/67ckj
- Li , B. , Xu , S. , and Peng , H. Eco-routing for Plug-In Hybrid Electric Vehicles IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC) Rhodes 2020 10.1109/ITSC45102.2020.9294577