no code implementations • 20 Oct 2023 • Junzhe Shi, Ulf Jakob Flø Aarsnes, Dagfinn Nærheim, Scott Moura
The online energy management system (EMS) is essential for these hybrid systems, tasked with controlling the energy flow and ensuring optimal system performance, encompassing fuel efficiency and mitigating fuel cell and battery degradation.
no code implementations • 9 Dec 2020 • Junzhe Shi, Min Tian, Sangwoo Han, Tung-Yan Wu, Yifan Tang
A highly accurate RCT estimation algorithm for electric vehicles is in high demand and will continue to be as EVs become more popular.
no code implementations • 28 Oct 2020 • Junzhe Shi, Bin Xu, Xingyu Zhou, Jun Hou
The Gradient Boost Decision Tree model is selected due to its best accuracy and high stability.
no code implementations • 27 Oct 2020 • Bin Xu, Junzhe Shi, Sixu Li, Huayi Li, Zhe Wang
Then, the result from a vehicle without ultracapacitor is used as the baseline, which is compared with the results from the vehicle with ultracapacitor using Q-learning, and two heuristic methods as the energy management strategies.
no code implementations • 27 Oct 2020 • Bin Xu, Jun Hou, Junzhe Shi, Huayi Li, Dhruvang Rathod, Zhe Wang, Zoran Filipi
This study aims to reduce the learning iterations of Q-learning in HEV application and improve fuel consumption in initial learning phases utilizing warm start methods.