The optimization and training processes of deep reinforcement learning (DRL) based
energy management strategy (EMS) can be very slow and resource-intensive. In this paper …

Committed to optimizing the fuel economy of hybrid electric vehicles (HEVs), improving the
working conditions of the engine, and promoting research on deep reinforcement learning …

As the performance of Energy Management Strategy (EMS) is crucial for the energy
efficiency of Hybrid Electric Vehicles (HEVs), a Deep Reinforcement Learning (DRL)-based …

Reinforcement learning is a new research hotspot in the energy management strategy. At
present, some problems in the application of reinforcement learning to energy management …

With the development of artificial intelligence, there has been a growing interest in machine
learning-based control strategy, among which reinforcement learning (RL) has opened up a …

Abstract Machine learning (ML)-based methods have attracted great attention in the multi-
objective optimization problems, which is the key challenge in the energy management …

Energy management strategies (EMSs) are essential for hybrid electric vehicles (HEVs), as
they can further exploit the potential of HEVs to save energy and reduce emissions …

Due to the high mileage and heavy load capabilities of hybrid commercial vehicles, energy
management becomes crucial in improving their fuel economy. In this paper, terrain …

This research proposes a reinforcement learning-based algorithm and a deep reinforcement
learning-based algorithm for energy management of a series hybrid electric tracked vehicle …

Energy management strategy (EMS) is critical to ensure the long-term energy economy of
hybrid electric vehicles. The classical deep reinforcement learning algorithms exist many …