Developing optimal control strategies with capability of real-time implementation for plug-in hybrid electric vehicles (PHEVs) has drawn explosive attention. In this study, a novel hierarchical control framework is proposed ...

In this paper, a rule learning based energy management strategy is proposed to achieve preferable energy consumption economy for fuel cell hybrid electric vehicles. Firstly, the optimal control sequence of fuel cell power ...

IEEE Remaining useful life (RUL) prediction of lithium-ion batteries plays an important role in intelligent battery management systems (BMSs). The current RUL prediction methods are mainly developed based on offline training, ...

Accurate modelling of particle shrinkage during biomass pyrolysis is key to the production of biochars with specific morphologies. Such biochars represent sustainable solutions to a variety of adsorption-dependent environmental ...

Adaptability to various driving conditions (TCs) is one of the essential indicators to assess the optimality of power management strategies (PMSs) of plug-in hybrid electric vehicles (PHEVs). In this study, a novel optimal ...

The ability of calcium phosphate (CaP) materials to induce bone formation varies with their physicochemical properties, with surface topography as one of the most crucial triggers. In view of the natural wound healing ...

With the development of connected and automated vehicles, eco-driving control is reckoned to generate unprecedented potential on energy-saving in electrified powertrain. In this paper, a data-driven based eco-driving control ...

Driving behaviors, induced by psychological activities and environment stimulation, impose the dominant impact on vehicle driving performance. To exhaustively improve the performance of electric vehicles (EVs), information ...