The growing need to alleviate the environmental impact of fossil fuels demands further
technical growth in fuel cell hybrid electric vehicles (FCHEVs). Due to the dynamic nature of …

In recent years, the severe environmental degradation and high levels of fossil fuel
consumption linked to conventional ship energy systems have drawn attention to the …

The increasing demands for reducing greenhouse emissions and improving fuel efficiency
of marine transportation have presented opportunities for electric ships. Due to the …

With the increasing penetration of renewable energy and flexible loads in smart grids, a
more complicated power system with high uncertainty is gradually formed, which brings …

Reinforcement learning (RL) is an increasingly popular technique for hybrid system energy
management. However, the existing review literature has not emphasized the training …

This paper introduces a new scalable multi-objective deep reinforcement learning (MODRL)
framework based on deep Q-networks. We develop a high-performance MODRL framework …

Due to the increasing impacts of ships pollutants on the environment and the preventive
laws that are tightening every day, the utilization of all-electric ships is a recent emerging …

Plug-in hybrid fuel cell and battery propulsion systems appear promising for decarbonising
transportation applications such as road vehicles and coastal ships. However, it is …

With the continuous promotion of energy saving and emission reduction policies, the
development of highly efficient and low emission green ships is the priority for the industry …

At present, Ship energy scheduling based on deep reinforcement learning (DRL) is an
important research direction in which Deep Q learning algorithm (DQN) has been …