Reinforcement learning-based real-time energy management for a hybrid tracked vehicle

Yuan Zou(Beijing Institute of Technology), Fengchun Sun(Kangwon National University), Dexing Liu(Beijing Institute of Technology), Teng Liu(Beijing Institute of Technology)
Applied Energy
March 23, 2016
10.1016/j.apenergy.2016.03.082
Cited by 245

Related Papers

Critical Review on the Battery State of Charge Estimation Methods for Electric Vehicles
|IEEE Access|2017|950
A review of supercapacitor modeling, estimation, and applications: A control/management perspective
|Renewable and Sustainable Energy Reviews|2017|921
State-of-Charge Estimation of the Lithium-Ion Battery Using an Adaptive Extended Kalman Filter Based on an Improved Thevenin Model
|IEEE Transactions on Vehicular Technology|2011|785
Lithium-ion battery aging mechanisms and diagnosis method for automotive applications: Recent advances and perspectives
|Renewable and Sustainable Energy Reviews|2020|699
Adaptive unscented Kalman filtering for state of charge estimation of a lithium-ion battery for electric vehicles
|Energy|2011|602