TY - GEN
T1 - New Energy Hybrid Environment Power Management System
T2 - 24th International Conference on Human-Computer Interaction, HCII 2022
AU - Tian, Yuyang
AU - Ye, Han
AU - Liao, Shaoyi (Stephen)
PY - 2022
Y1 - 2022
N2 - Compared with batteries, supercapacitors have high density, and it can work in a wider range of climatic conditions. In addition, ultracapacitors have lower internal resistance and longer life span. Our study aims to design a new energy hybrid management system to solve the problem of the combination of batteries and supercapacitors in the most efficient way. Also, by using the real driving data, we can test how the system interact with the drivers on different roads. The efficient multi-energy power management system based on supercapacitors and batteries includes: bidirectional DC/DC (Direct Current to Direct Current) converters, battery modules and supercapacitor modules, ECUs (Electronic Control Units), motor controllers, motors, etc. We used models created in the existing DSpace-based simulation environment to detect and control the power flow in various driving scenarios. As a result, the hybrid energy vehicle effectively improves the steep acceleration, reduces the instantaneous high current output of lead-acid batteries, and effectively protects the power battery. We obtained a complete set of intelligent control strategies for energy management and verified the effectiveness of the designed optimal energy management control algorithm.
AB - Compared with batteries, supercapacitors have high density, and it can work in a wider range of climatic conditions. In addition, ultracapacitors have lower internal resistance and longer life span. Our study aims to design a new energy hybrid management system to solve the problem of the combination of batteries and supercapacitors in the most efficient way. Also, by using the real driving data, we can test how the system interact with the drivers on different roads. The efficient multi-energy power management system based on supercapacitors and batteries includes: bidirectional DC/DC (Direct Current to Direct Current) converters, battery modules and supercapacitor modules, ECUs (Electronic Control Units), motor controllers, motors, etc. We used models created in the existing DSpace-based simulation environment to detect and control the power flow in various driving scenarios. As a result, the hybrid energy vehicle effectively improves the steep acceleration, reduces the instantaneous high current output of lead-acid batteries, and effectively protects the power battery. We obtained a complete set of intelligent control strategies for energy management and verified the effectiveness of the designed optimal energy management control algorithm.
KW - Energy management systems
KW - New energy
KW - Simulation
KW - System design
UR - http://www.scopus.com/inward/record.url?scp=85142716441&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85142716441&origin=recordpage
U2 - 10.1007/978-3-031-18158-0_27
DO - 10.1007/978-3-031-18158-0_27
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 978-3-031-18157-3
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 362
EP - 375
BT - HCI International 2022 – Late Breaking Papers: HCI for Today’s Community and Economy
A2 - Rauterberg, Matthias
A2 - Nah, Fiona Fui-Hoon
A2 - Siau, Keng
A2 - Krömker, Heidi
A2 - Wei, June
A2 - Salvendy, Gavriel
PB - Springer, Cham
Y2 - 26 June 2022 through 1 July 2022
ER -
