In this work, we propose a deep reinforcement learning framework of the HEV power management with the aim of improving fuel economy. The DRL technique is ...
In this work, we propose a deep reinforcement learning framework of the HEV power management with the aim of improving fuel economy. The DRL technique is ...
The thesis presents a deep reinforcement learning (DRL) based technique, which can develop an optimal policy to effectively reduce vehicle fuel consumption by ...
Sep 22, 2023 · In this work, the eco-driving problem is formulated as a Partially Observable Markov Decision Process (POMDP), which is then solved with a state ...
Mar 23, 2024 · Recently, the DQL was employed for the energy management of electric vehicles, achieving satisfying performance concerning the minimization of ...
In this work, we propose a deep reinforcement learning framework of the HEV power management with the aim of improving fuel economy. The DRL technique is ...
Oct 7, 2020 · The framework includes: a database, a preprocessing module, a vehicle model and an online Bayesian algorithm module. It uses historical 0.2 Hz ...
A deep reinforcement learning approach to energy management ...
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This paper is aiming at addressing the energy optimization control issue using reinforcement learning algorithms.
Fingerprint. Dive into the research topics of 'A deep reinforcement learning framework for optimizing fuel economy of hybrid electric vehicles'.
The eco-driving problem is formulated as a Partially Observable Markov Decision Process (POMDP), which is then solved with a state-of-art Deep Reinforcement ...