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 …

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 …

Advanced algorithms can promote the development of energy management strategies
(EMSs) as a key technology in hybrid electric vehicles (HEVs). Reinforcement learning (RL) …

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 …

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 …

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 …

In this article, a heuristic deep reinforcement learning (DRL) control strategy is proposed for
the energy management of the series hybrid electric vehicle (SHEV). First, the powertrain …

Considering physical constraints in online optimization and training safety is a challenge for
the implementation of the deep reinforcement learning (DRL) algorithm. Especially for the …

A novel deep reinforcement learning (DRL) control framework for the energy management
strategy of the series hybrid electric tracked vehicle (SHETV) is proposed in this paper …

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 …