Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
In electric vehicles, as in hybrids vehicles, a very important factor affecting the energy efficiency of the power-train is the ability to use the regenerative braking energy. Depending on the settings available in electric vehicles, the driver can choose different modes of operation: switch off the regenerative braking mode altogether, select the intensity of regenerative braking, or leave the control system in automatic mode. The last mode is often the only one available on eclectic vehicles, so the driver cannot decide whether to switch off or increase intensity of the regenerative braking. This paper presents a new method for evaluating the energy efficiency of electric vehicle powertrains under urban operating conditions. The presented method uses a procedure for mapping the operating conditions allowing to determine the reference level of energy consumption in relation to those recorded during the identification tests. Identification tests were carried out in the Tri-City area using electric vehicles of different purposes and operating parameters. Performed tests allowed to evaluate the regenerative braking efficiency of tested vehicle, which varies over a relatively wide range, for vehicle A from 33 to 77%, for vehicle B from 27 to 55% and for vehicle C from 36 to 58%. It can be concluded that one of the main factors determining the regenerative braking efficiency is the level of state of charge of the accumulator and the management algorithm used by the vehicle for controlling this parameter.
Czasopismo
Rocznik
Tom
Strony
28--34
Opis fizyczny
Bibliogr. 21 poz., 1 rys., wykr.
Twórcy
autor
- Faculty of Mechanical Engineering, Gdańsk University of Technology, Poland
autor
- BMG Goworowski, Gdynia, Poland
Bibliografia
- [1] Alves J, Baptista PC, Gonçalves GA, Duarte GO. Indirect methodologies to estimate energy use in vehicles: application to battery electric vehicles. Energy Convers Manage. 2016; 124:116-129. https://doi.org/10.1016/j.enconman.2016.07.014
- [2] Andrych-Zalewska M, Chłopek Z, Merkisz J, Pielecha J. Analysis of the operation states of internal combustion engine in the Real Driving Emissions test. Archives of Transport. 2022;61(1):71-88. https://doi.org/10.5604/01.3001.0015.8162
- [3] Berzi L, Delogu M, Pierini M. Development of driving cycles for electric vehicles in the context of the city of Florence. Transport Res D-Tr E. 2016;47:299-322. https://doi.org/10.1016/j.trd.2016.05.010
- [4] Brady J, O’Mahony M. Development of a driving cycle to evaluate the energy economy of electric vehicles in urban areas. Appl Energ. 2016;177:165-178. https://doi.org/10.1016/j.apenergy.2016.05.094
- [5] Cieslik W, Zawartowski J, Fuc P. The Impact of the drive mode of a hybrid drive system on the share of electric mode in the RDC test. SAE Technical Paper 2020-01-2249. 2020. https://doi.org/10.4271/2020-01-2249
- [6] Damiani L, Repetto M, Prato AP. Improvement of powertrain efficiency through energy breakdown analysis. Appl Energ. 2014;121:252-263. https://doi.org/10.1016/j.apenergy.2013.12.067
- [7] Fiori C, Ahn K, Rakha HA. Power-based electric vehicle energy consumption model: model development and validation. Appl Energ. 2016;168:257-268. https://doi.org/10.1016/j.apenergy.2016.01.097
- [8] Fiori C, Arcidiacono V, Fontaras G, Makridis M, Mattas K, Marzano V et al. The effect of electrified mobility on the relationship between traffic conditions and energy consumption. Transport Res D-Tr E. 2019;67:275-290. https://doi.org/10.1016/j.trd.2018.11.018
- [9] Galvin R. Energy consumption effects of speed and acceleration in electric vehicles: laboratory case studies and implications for drivers and policymakers. Transport Res D-Tr E. 2017;53:234-248. https://doi.org/10.1016/j.trd.2017.04.020
- [10] Huang J, Qin D, Peng Z. Effect of energy-regenerative braking on electric vehicle battery thermal management and control method based on simulation investigation. Energy Convers Manage. 2015;105:1157-1165. https://doi.org/10.1016/j.enconman.2015.08.080
- [11] Kropiwnicki J, Gawłas T. Estimation of the regenerative braking process efficiency in electric vehicles. Acta Mechanica et Automatica. 2023;17(2):303-310. https://doi.org/10.2478/ama-2023-0035
- [12] Kropiwnicki J, Kneba Z, Ziółkowski M. Test for assessing the energy efficiency of vehicles with internal combustion engines. Int J Automot Technol. 2013;14(3):479-487. https://doi.org/10.1007/s12239-013-0052-9
- [13] Kropiwnicki J. A unified approach to the analysis of electric energy and fuel consumption of cars in city traffic. Energy. 2019;182:1045-1057. https://doi.org/10.1016/j.energy.2019.06.114
- [14] Li L, Li X, Wang X, Song J, He K, Li C. Analysis of down-shift’s improvement to energy efficiency of an electric vehicle during regenerative braking. Appl Energ. 2016;176:125-137. https://doi.org/10.1016/j.apenergy.2016.05.042
- [15] Li L, You S, Yang C, Yan B, Song J, Chen Z. Driving-behavior-aware stochastic model predictive control for plug-in hybrid electric buses. Appl Energ. 2016;162:868-879. https://doi.org/10.1016/j.apenergy.2015.10.152
- [16] Liu W, Qi H, Liu X, Wang Y. Evaluation of regenerative braking based on single-pedal control for electric vehicles. Front Mech Eng. 2020;15(1):166-179. https://doi.org/10.1007/s11465-019-0546-x
- [17] Mamala J, Śmieja M, Prażnowski K. Analysis of the total unit energy consumption of a car with a hybrid drive system in real operating conditions. Energies. 2021;14:3966. https://doi.org/10.3390/en14133966
- [18] Pielecha I, Cieślik W, Fluder K. Analysis of energy management strategies for hybrid electric vehicles in urban driving conditions. Combustion Engines. 2018;173(2):14-18. https://doi.org/10.19206/CE-2018-203
- [19] Pielecha I, Cieślik W, Szałek A. The use of electric drive in urban driving conditions using a hydrogen powered vehicle - Toyota Mirai. Combustion Engines. 2018;172(1):51-58. https://doi.org/10.19206/CE-2018-106
- [20] Qian KF, Liu XT. Hybrid optimization strategy for lithium-ion battery’s state of charge/health using joint of dual Kalman filter and modified sine-cosine algorithm. J Energy Storage. 2021;44:103319. https://doi.org/10.1016/j.est.2021.103319
- [21] Qiu C, Wang G. New evaluation methodology of regenerative braking contribution to energy efficiency improvement of electric vehicles. Energy Convers Manage. 2016;119:389-398. https://doi.org/10.1016/j.enconman.2016.04.044
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b44ef8ab-60ae-42da-a80b-e3198f2c9c93