Dynamic Generation of Recommendations for EV Battery Health
作者： Markus Eider , Andreas Berl
DOI: 10.23919/EETA.2018.8493182
关键词:
摘要: Electric vehicles equipped with Lithium-ion batteries face performance loss due to battery ageing. This effect can be actively influenced through behaviour introduced by vehicle users. Therefore, this paper proposes a dynamic recommendation architecture automatically generate recommendations in order prolong lifetime.We propose as well requirements for them. The suggest certain user specific chronological scope the future weight based on their impact maintaining health.Furthermore, we present an exemplary architecture, requirements. Using historical electric driving data, it derive recommendations.
sci-hub.se 参考文章(37)
Vaibhav Ankush Kachore, J. Lakshmi, S.K. Nandy, Location Obfuscation for Location Data Privacy world congress on services. pp. 213- 220 ,(2015) , 10.1109/SERVICES.2015.39
Gillian Lacey, Tianxiang Jiang, Ghanim Putrus, Richard Kotter, The effect of cycling on the state of health of the electric vehicle battery international universities power engineering conference. pp. 1- 7 ,(2013) , 10.1109/UPEC.2013.6715031
Seyed Mohammad Rezvanizaniani, Zongchang Liu, Yan Chen, Jay Lee, Review and recent advances in battery health monitoring and prognostics technologies for electric vehicle (EV) safety and mobility Journal of Power Sources. ,vol. 256, pp. 110- 124 ,(2014) , 10.1016/J.JPOWSOUR.2014.01.085
J. Vetter, P. Novák, M.R. Wagner, C. Veit, K.-C. Möller, J.O. Besenhard, M. Winter, M. Wohlfahrt-Mehrens, C. Vogler, A. Hammouche, Ageing mechanisms in lithium-ion batteries Journal of Power Sources. ,vol. 147, pp. 269- 281 ,(2005) , 10.1016/J.JPOWSOUR.2005.01.006
Jeremy S. Neubauer, Eric Wood, Ahmad Pesaran, A Second Life for Electric Vehicle Batteries: Answering Questions on Battery Degradation and Value SAE International Journal of Materials and Manufacturing. ,vol. 8, pp. 544- 553 ,(2015) , 10.4271/2015-01-1306
Kong Soon Ng, Chin-Sien Moo, Yi-Ping Chen, Yao-Ching Hsieh, Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries Applied Energy. ,vol. 86, pp. 1506- 1511 ,(2009) , 10.1016/J.APENERGY.2008.11.021
Lluc Canals Casals, Adrian Miguel Schiffer Gonzalez, Beatriz Garcia, Jordi Llorca, PHEV Battery Aging Study Using Voltage Recovery and Internal Resistance From Onboard Data IEEE Transactions on Vehicular Technology. ,vol. 65, pp. 4209- 4216 ,(2016) , 10.1109/TVT.2015.2459760
Xiaosong Hu, Jiuchun Jiang, Dongpu Cao, Bo Egardt, Battery Health Prognosis for Electric Vehicles Using Sample Entropy and Sparse Bayesian Predictive Modeling IEEE Transactions on Industrial Electronics. ,vol. 63, pp. 1- 1 ,(2015) , 10.1109/TIE.2015.2461523
Gae-won You, Sangdo Park, Dukjin Oh, Real-time state-of-health estimation for electric vehicle batteries: A data-driven approach Applied Energy. ,vol. 176, pp. 92- 103 ,(2016) , 10.1016/J.APENERGY.2016.05.051
C. Dudézert, Y. Reynier, J.-M. Duffault, S. Franger, Fatigue damage approach applied to Li-ion batteries ageing characterization Materials Science and Engineering B-advanced Functional Solid-state Materials. ,vol. 213, pp. 177- 189 ,(2016) , 10.1016/J.MSEB.2016.04.017