The real-time control of energy management strategy (EMS) is becoming increasingly
challenging as the complexity of the model and control strategy increases. To address this …

Abstract Model predictive control (MPC) is one of the most promising energy management
strategies for hybrid electric vehicles. However, owing to constructive complexity, the …

This paper provides a comprehensive review of machine learning strategies and
optimization formulations employed in energy management systems (EMS) tailored for plug …

A new equivalent consumption minimization strategy (ECMS) is proposed for a hybrid
electric vehicle in which the equivalent factor varies dynamically with the current speed and …

Ship collision risk prediction is vital for maritime traffic surveillance, which determines if there
is a sustainable and efficient development of the shipping industry. In order to solve the …

This paper proposes a cost-effective power management strategy utilizing the data provided
by V2I communication techniques for dual electric machine coupling propulsion trucks. We …

For the design of the hybrid electric vehicles, the strong coupling between plant parameters
and controller parameters turns the problem into a multi-layered challenge. If handled …

The fuel economy of hybrid electric vehicles is inextricably linked to the energy management
strategy (EMS). In this study, a practicality-oriented learning-based EMS for a power-split …

With the rapid development of machine learning, deep reinforcement learning (DRL)
algorithms have recently been widely used for energy management in hybrid electric urban …

The battery supercapacitor hybrid energy storage system (HESS) based electric vehicles
(EVs) require an efficient online energy management system (EMS) to enhance the battery …