Object-oriented mathematical modeling for estimating electric vehicle’s range using modelica
Electric vehicles (EVs) offer a great alternative for decarbonizing the transport sector. However, insufficient recharging infrastructure and limited range increase the driver’s ‘range anxiety’. Furthermore, the autonomy information provided by vehicle manufacturers differs from the range obtained u...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2018
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/8901
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/8901
- Palabra clave:
- Electric vehicles
Library
Modelica
Modeling
Range
Automobile manufacture
Commercial vehicles
Electric vehicles
Energy utilization
Estimation
Libraries
Models
Computational model
Electric Vehicles (EVs)
Modelica
Modeling and simulating
Object-oriented modeling languages
Range
Specification sheets
Vehicle manufacturers
Modeling languages
- Rights
- restrictedAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
| id |
UTB2_026a32bd285d57e3cc4b419f96c10df3 |
|---|---|
| oai_identifier_str |
oai:repositorio.utb.edu.co:20.500.12585/8901 |
| network_acronym_str |
UTB2 |
| network_name_str |
Repositorio Institucional UTB |
| repository_id_str |
|
| dc.title.none.fl_str_mv |
Object-oriented mathematical modeling for estimating electric vehicle’s range using modelica |
| title |
Object-oriented mathematical modeling for estimating electric vehicle’s range using modelica |
| spellingShingle |
Object-oriented mathematical modeling for estimating electric vehicle’s range using modelica Electric vehicles Library Modelica Modeling Range Automobile manufacture Commercial vehicles Electric vehicles Energy utilization Estimation Libraries Models Computational model Electric Vehicles (EVs) Modelica Modeling and simulating Object-oriented modeling languages Range Specification sheets Vehicle manufacturers Modeling languages |
| title_short |
Object-oriented mathematical modeling for estimating electric vehicle’s range using modelica |
| title_full |
Object-oriented mathematical modeling for estimating electric vehicle’s range using modelica |
| title_fullStr |
Object-oriented mathematical modeling for estimating electric vehicle’s range using modelica |
| title_full_unstemmed |
Object-oriented mathematical modeling for estimating electric vehicle’s range using modelica |
| title_sort |
Object-oriented mathematical modeling for estimating electric vehicle’s range using modelica |
| dc.contributor.editor.none.fl_str_mv |
Serrano C. J.E. Martínez-Santos, Juan Carlos |
| dc.subject.keywords.none.fl_str_mv |
Electric vehicles Library Modelica Modeling Range Automobile manufacture Commercial vehicles Electric vehicles Energy utilization Estimation Libraries Models Computational model Electric Vehicles (EVs) Modelica Modeling and simulating Object-oriented modeling languages Range Specification sheets Vehicle manufacturers Modeling languages |
| topic |
Electric vehicles Library Modelica Modeling Range Automobile manufacture Commercial vehicles Electric vehicles Energy utilization Estimation Libraries Models Computational model Electric Vehicles (EVs) Modelica Modeling and simulating Object-oriented modeling languages Range Specification sheets Vehicle manufacturers Modeling languages |
| description |
Electric vehicles (EVs) offer a great alternative for decarbonizing the transport sector. However, insufficient recharging infrastructure and limited range increase the driver’s ‘range anxiety’. Furthermore, the autonomy information provided by vehicle manufacturers differs from the range obtained under real-driving conditions. In order to estimate the actual range of an EV under different driving profiles, accurate computational modeling is required. This paper presents a library for modeling and simulating EVs using the object-oriented modeling language Modelica that allows calculating the energy consumption and the impact of different driving behaviors on the vehicle’s driving range. Each vehicle’s model only requires generic parameters that can be obtained from the vehicle’s manufacturer’s specification sheet. The parameters of the example models have been calibrated using vehicle parameters found in the literature for several commercial vehicles. © Springer Nature Switzerland AG 2018. |
| publishDate |
2018 |
| dc.date.issued.none.fl_str_mv |
2018 |
| dc.date.accessioned.none.fl_str_mv |
2020-03-26T16:32:35Z |
| dc.date.available.none.fl_str_mv |
2020-03-26T16:32:35Z |
| dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_c94f |
| dc.type.driver.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
| dc.type.hasversion.none.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.spa.none.fl_str_mv |
Conferencia |
| status_str |
publishedVersion |
| dc.identifier.citation.none.fl_str_mv |
Communications in Computer and Information Science; Vol. 885, pp. 444-458 |
| dc.identifier.isbn.none.fl_str_mv |
9783319989976 |
| dc.identifier.issn.none.fl_str_mv |
18650929 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/8901 |
| dc.identifier.doi.none.fl_str_mv |
10.1007/978-3-319-98998-3_34 |
| dc.identifier.instname.none.fl_str_mv |
Universidad Tecnológica de Bolívar |
| dc.identifier.reponame.none.fl_str_mv |
Repositorio UTB |
| dc.identifier.orcid.none.fl_str_mv |
56682770100 55609096600 |
| identifier_str_mv |
Communications in Computer and Information Science; Vol. 885, pp. 444-458 9783319989976 18650929 10.1007/978-3-319-98998-3_34 Universidad Tecnológica de Bolívar Repositorio UTB 56682770100 55609096600 |
| url |
https://hdl.handle.net/20.500.12585/8901 |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.conferencedate.none.fl_str_mv |
26 September 2018 through 28 September 2018 |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_16ec |
| dc.rights.uri.none.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| dc.rights.accessrights.none.fl_str_mv |
info:eu-repo/semantics/restrictedAccess |
| dc.rights.cc.none.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
| rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ Atribución-NoComercial 4.0 Internacional http://purl.org/coar/access_right/c_16ec |
| eu_rights_str_mv |
restrictedAccess |
| dc.format.medium.none.fl_str_mv |
Recurso electrónico |
| dc.format.mimetype.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
Springer Verlag |
| publisher.none.fl_str_mv |
Springer Verlag |
| dc.source.none.fl_str_mv |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054351813&doi=10.1007%2f978-3-319-98998-3_34&partnerID=40&md5=253bc33e43740b4cb904461c4f200a4f |
| institution |
Universidad Tecnológica de Bolívar |
| dc.source.event.none.fl_str_mv |
13th Colombian Conference on Computing, CCC 2018 |
| bitstream.url.fl_str_mv |
https://repositorio.utb.edu.co/bitstream/20.500.12585/8901/1/MiniProdInv.png |
| bitstream.checksum.fl_str_mv |
0cb0f101a8d16897fb46fc914d3d7043 |
| bitstream.checksumAlgorithm.fl_str_mv |
MD5 |
| repository.name.fl_str_mv |
Repositorio Institucional UTB |
| repository.mail.fl_str_mv |
repositorioutb@utb.edu.co |
| _version_ |
1814021705395339264 |
| spelling |
Serrano C. J.E.Martínez-Santos, Juan CarlosDomínguez Jiménez, Juan AntonioCampillo Jiménez, Javier Eduardo2020-03-26T16:32:35Z2020-03-26T16:32:35Z2018Communications in Computer and Information Science; Vol. 885, pp. 444-458978331998997618650929https://hdl.handle.net/20.500.12585/890110.1007/978-3-319-98998-3_34Universidad Tecnológica de BolívarRepositorio UTB5668277010055609096600Electric vehicles (EVs) offer a great alternative for decarbonizing the transport sector. However, insufficient recharging infrastructure and limited range increase the driver’s ‘range anxiety’. Furthermore, the autonomy information provided by vehicle manufacturers differs from the range obtained under real-driving conditions. In order to estimate the actual range of an EV under different driving profiles, accurate computational modeling is required. This paper presents a library for modeling and simulating EVs using the object-oriented modeling language Modelica that allows calculating the energy consumption and the impact of different driving behaviors on the vehicle’s driving range. Each vehicle’s model only requires generic parameters that can be obtained from the vehicle’s manufacturer’s specification sheet. The parameters of the example models have been calibrated using vehicle parameters found in the literature for several commercial vehicles. © Springer Nature Switzerland AG 2018.Recurso electrónicoapplication/pdfengSpringer Verlaghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/restrictedAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_16echttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85054351813&doi=10.1007%2f978-3-319-98998-3_34&partnerID=40&md5=253bc33e43740b4cb904461c4f200a4f13th Colombian Conference on Computing, CCC 2018Object-oriented mathematical modeling for estimating electric vehicle’s range using modelicainfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionConferenciahttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_c94fElectric vehiclesLibraryModelicaModelingRangeAutomobile manufactureCommercial vehiclesElectric vehiclesEnergy utilizationEstimationLibrariesModelsComputational modelElectric Vehicles (EVs)ModelicaModeling and simulatingObject-oriented modeling languagesRangeSpecification sheetsVehicle manufacturersModeling languages26 September 2018 through 28 September 2018Alexander, R., Solving ordinary differential equations I: Nonstiff problems (E. Hairer, S.P. Norsett, and G. Wanner) (1990) SIAM Rev, 32 (3), p. 485Barcellona, S., Piegari, L., Improvement of Evs Range by Hybrid Storage UnitsBauml, T., Simic, D., Simulation and comparison of different energy management strategies of a series hybrid electric vehicle (2008) 2008 IEEE Vehicle Power and Propulsion Conference, VPPC 2008, pp. 1-5Björnsson, L.H., Karlsson, S., The potential for brake energy regeneration under swedish conditions (2016) Appl. Energy, 168, pp. 75-84Braun, A., Rid, W., Energy consumption of an electric and an internal combustion passenger car (2017) A Comparative Case Study from Real World Data on the Erfurt Circuit in Germany. Transp. Res. Procedia, 27, pp. 468-475. , https://doi.org/10.1016/j.trpro.2017.12.044.http://linkinghub.elsevier.com/retrieve/pii/S2352146517309419Bunce, L., Harris, M., Burgess, M., Charge up then charge out? Drivers perceptions and experiences of electric vehicles in the UK (2014) Transp. Res. Part A: Policy Pract., 59, pp. 278-287. , http://linkinghub.elsevier.com/retrieve/pii/S0965856413002395, https://doi.org/10.1016/j.tra.2013.12.001Carter, R., Cruden, A., Hall, P.J., Optimizing for efficiency or battery life in a battery/supercapacitor electric vehicle (2012) IEEE Trans. Vehic. Technol., 61 (4), pp. 1526-1533Cellier, F.E., Kofman, E., (2006) Continuous System Simulation, , https://doi.org/10.1007/0-387-30260-3, Springer, HeidelbergChen, M., Rincon-Mora, G.A., Accurate electrical battery model capable of predicting runtime and IV performance (2006) IEEE Trans. Energy Convers., 21 (2), pp. 504-511Daina, N., Sivakumar, A., Polak, J.W., Modelling electric vehicles use: A survey on the methods (2017) Renew. Sustain. Energy Rev., 68, pp. 447-460. , https://doi.org/10.1016/j.rser.2016.10.005.http://linkinghub.elsevier.com/retrieve/pii/S1364032116306566Dore, C., UK emissions of air pollutants 1970 to 2001 (2003) National Atmospheric Emissions InventoryEgbue, O., Long, S., Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions (2012) Energy Policy, 48, pp. 717-729. , https://doi.org/10.1016/j.enpol.2012.06.009.http://linkinghub.elsevier.com/retrieve/pii/S0301421512005162Einhorn, M., Conte, F.V., Kral, C., Niklas, C., Popp, H., Fleig, J., A modelica library for simulation of electric energy storages (2011) Proceedings of the 8Th International Modelica Conference, 20th–22nd March. Technical UniveristyDresden, Germany, pp. 436-445. , Linkping University Electronic PressEnang, W., Bannister, C., Modelling and control of hybrid electric vehicles (A comprehensive review) (2017) Renew. Sustain. Energy Rev., 74, pp. 1210-1239. , https://doi.org/10.1016/j.rser.2017.01.075.http://linkinghub.elsevier.com/retrieve/pii/S1364032117300850Fritzson, P., (2010) Principles of Object-Oriented Modeling and Simulation with Modelica 3.2, , Wiley, HobokenGerami Tehrani, M., (2013) Energy Efficiency Consideration in Electric Vehicle TransmissionGonder, J., Earleywine, M., Sparks, W., Analyzing vehicle fuel saving opportunities through intelligent driver feedback. SAE (2012) Int. J. Passeng. Cars-Electron. Electr. Syst, 5 (201201-0494), pp. 450-461Grunditz, E.A., Thiringer, T., Performance analysis of current bevs based on a comprehensive review of specifications (2016) IEEE Trans. Transp. Electrif., 2 (3), pp. 270-289Guirong, Z., Henghai, Z., Houyu, L., The driving control of pure electric vehicle (2011) Procedia Environ. Sci., 10, pp. 433-438. , https://doi.org/10.1016/j.proenv.2011.09.071, http://www.sciencedirect.com/science/article/pii/S1878029611002660. 2011 3rd International Conference on Environmental Science and Information Application Technology ESIAT 2011Guo, N., Chen, Z., Wu, Y., Shen, J., Xiao, R., A Novel Velocity Forecast Method for Improving Predictive Energy Management of Plug-In Hybrid Electric VehiclesGuzzella, L., Sciarretta, A., (2007) Vehicle Propulsion Systems, 1. , https://doi.org/10.1007/978-3-540-74692-8, Springer, HeidelbergHayes, J.G., de Oliveira, R.P.R., Vaughan, S., Egan, M.G., Simplified electric vehicle power train models and range estimation (2011) 2011 IEEE Vehicle Power and Propulsion Conference, pp. 1-5. , https://doi.org/10.1109/VPPC.2011.6043163, SeptemberHuertas, J.I., Díaz, J., Cordero, D., Cedillo, K., A new methodology to determine typical driving cycles for the design of vehicles power trains (2018) Int. J. Interact. Des. Manuf. (Ijidem), 12 (1), pp. 319-326International Energy Agency: Global EV Outlook 2017 (2017) Two Million and Counting, , www.iea.org, Technical reportLaitinen, H., Saalasti, O.Y., Lajunen, A., Tammi, K., (2017) Improving Electric Vehicle Energy Efficiency with Two-Speed GearboxLangbroek, J.H., Franklin, J.P., Susilo, Y.O., The effect of policy incentives on electric vehicle adoption (2016) Energy Policy, 94, pp. 94-103. , https://doi.org/10.1016/j.enpol.2016.03.050.http://linkinghub.elsevier.com/retrieve/pii/S0301421516301550Li, Y., Zhang, X., Yang, J., A cost-effective regenerative braking system for electric vehicles driven by induction machine (2016) 2016 IEEE Vehicle Power and Propulsion Conference (VPPC), pp. 1-5Scoltock, J., Calderon-Lopez, G., Forsyth, A.J., Topology and Magnetics Optimisation for a 100-Kw Bi-Directional DC-DC ConverterTrentelman, T., Sutherland, J., Oizumi, K., Aoyama, K., Modelica based naval architecture library for small autonomous boat design (2017) Proceedings of the 12Th International Modelica Conference, 132, pp. 643-652. , Prague, Czech Republic, 15–17 May 2017, Linköping University Electronic PressVassileva, I., Campillo, J., Adoption barriers for electric vehicles: Experiences from early adopters in Sweden (2017) Energy, 120, pp. 632-641. , https://doi.org/10.1016/j.energy.2016.11.119.http://linkinghub.elsevier.com/retrieve/pii/S0360544216317741http://purl.org/coar/resource_type/c_c94fTHUMBNAILMiniProdInv.pngMiniProdInv.pngimage/png23941https://repositorio.utb.edu.co/bitstream/20.500.12585/8901/1/MiniProdInv.png0cb0f101a8d16897fb46fc914d3d7043MD5120.500.12585/8901oai:repositorio.utb.edu.co:20.500.12585/89012023-05-26 16:30:25.275Repositorio Institucional UTBrepositorioutb@utb.edu.co |