Energy consumption forecast and charging demand alert based on operation condition clustering and control variable method

Xuejing Huang; Jun Jia; Wei Xiao; Ji Zhao; Zhe Chen; Zongyang Liu; Jiaqi Li

doi:10.1051/e3sconf/202021801008

All issues

Volume 218 (2020)

E3S Web Conf., 218 (2020) 01008

References

Open Access

Issue		E3S Web Conf. Volume 218, 2020 2020 International Symposium on Energy, Environmental Science and Engineering (ISEESE 2020)


Article Number		01008
Number of page(s)		6
Section		Research on Energy Technology Application and Consumption Structure
DOI		https://doi.org/10.1051/e3sconf/202021801008
Published online		11 December 2020

Official website of the Ministry of Industry and Information Technology. The Ministry of Industry and Information Technology held a kick-off meeting for the preparation of the “New Energy Automobile Industry Development Plan (2021-2035)” [J]. People’s Public Transport, (2): 27-27 (2019) [Google Scholar]
National Energy Administration. Annual Report of China Electric Vehicle Charging Infrastructure Promotion Alliance [EB/OL]. http://www.nea.gov.cn/2017-6/19/c_136376732.html [Google Scholar]
Xiao W, Xu H., Jia J*, Feng F, & Wang W. State of Health Estimation Framework of Li-on Battery Based on Improved Gaussian Process Regression for Real Car Data. IOP Conference Series: Materials Science and Engineering, 793, 012063 (2020). [CrossRef] [Google Scholar]
Jia J, Deng Z, Hu X, et al. Data-driven comprehensive scoring of lithium-ion battery health status and abnormal battery screening[J]. Chinese Journal of Mechanical Engineering, (to be published). [Google Scholar]
Xiao W, Zhong W, Shu X, et al. Estimation and application of battery state of health (SoH) based on big data[J]. Journal of Automotive Safety and Energy, 10(01):105-109 (2019) [Google Scholar]
Yan J, Xiao W, Jia J, et al. Remaining driving range data-driven algorithm based on energy consumption parameter identification and road condition prediction [J/OL]. Journal of Chongqing University of Technology (Natural Science): 1-13 (2020) [Google Scholar]
Ma Z, Sun D. Energy Recovery Strategy Based on Ideal Braking Force Distribution for Regenerative Braking System of a Four-Wheel Drive Electric Vehicle[J]. IEEE Access, PP(99):1-1 (2020) [Google Scholar]
Chen H, Yang S, Pei J, et al. Collaborative filtering recommendation algorithm based on matrix factorization and Meanshift clustering[J]. Computer Science and Applications, 010(004):P. 649-658 (2020). [CrossRef] [Google Scholar]
Cai T, Tang H. Summary of the least square fitting principle of Savitzky-Golay smoothing filter[J]. Digital Communications, 38(01):63-68 (2011) [Google Scholar]
Hu X, Feng F, Liu K. State estimation for advanced battery management: Key challenges and future trends[J]. Renewable & Sustainable Energy Reviews, 114(OCT.):109334.1-109334.13 (2019) [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.

[1] Official website of the Ministry of Industry and Information Technology. The Ministry of Industry and Information Technology held a kick-off meeting for the preparation of the “New Energy Automobile Industry Development Plan (2021-2035)” [J]. People’s Public Transport, (2): 27-27 (2019) [Google Scholar]

[2] National Energy Administration. Annual Report of China Electric Vehicle Charging Infrastructure Promotion Alliance [EB/OL]. http://www.nea.gov.cn/2017-6/19/c_136376732.html [Google Scholar]

[3] Xiao W, Xu H., Jia J*, Feng F, & Wang W. State of Health Estimation Framework of Li-on Battery Based on Improved Gaussian Process Regression for Real Car Data. IOP Conference Series: Materials Science and Engineering, 793, 012063 (2020). [CrossRef] [Google Scholar]

[4] Jia J, Deng Z, Hu X, et al. Data-driven comprehensive scoring of lithium-ion battery health status and abnormal battery screening[J]. Chinese Journal of Mechanical Engineering, (to be published). [Google Scholar]

[5] Xiao W, Zhong W, Shu X, et al. Estimation and application of battery state of health (SoH) based on big data[J]. Journal of Automotive Safety and Energy, 10(01):105-109 (2019) [Google Scholar]

[6] Yan J, Xiao W, Jia J, et al. Remaining driving range data-driven algorithm based on energy consumption parameter identification and road condition prediction [J/OL]. Journal of Chongqing University of Technology (Natural Science): 1-13 (2020) [Google Scholar]

[7] Ma Z, Sun D. Energy Recovery Strategy Based on Ideal Braking Force Distribution for Regenerative Braking System of a Four-Wheel Drive Electric Vehicle[J]. IEEE Access, PP(99):1-1 (2020) [Google Scholar]

[8] Chen H, Yang S, Pei J, et al. Collaborative filtering recommendation algorithm based on matrix factorization and Meanshift clustering[J]. Computer Science and Applications, 010(004):P. 649-658 (2020). [CrossRef] [Google Scholar]

[9] Cai T, Tang H. Summary of the least square fitting principle of Savitzky-Golay smoothing filter[J]. Digital Communications, 38(01):63-68 (2011) [Google Scholar]

[10] Hu X, Feng F, Liu K. State estimation for advanced battery management: Key challenges and future trends[J]. Renewable & Sustainable Energy Reviews, 114(OCT.):109334.1-109334.13 (2019) [Google Scholar]