Data Driven Transferred Energy Management Strategy for Hybrid Electric Vehicles via Deep Reinforcement Learning

Real-time applications of energy management strategies (EMSs) in hybrid electric vehicles are the harshest requirements for researchers and engineers . Inspired by the excellent problem-solving capabilities of deep reinforcement learning (DRL), this paper proposes a real-time EMS via incorporating the DRL method and transfer learning (TL) The EMSs related to the target driving cycles are estimated and compared in different training conditions . Simulation results indicate that the presented transfer DRL-based EMS could effectively reduce time consumption and guarantee control performance. Simulation results indicated that the present transfer DHL-based . EMSs could effectively . effectively reduce . time consumption, . guarantee . control performance and . guarantee control . performance. The paper concludes. The authors of this paper

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Keywords : time - control - transfer - drl - learning -

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