Volume 25: Accelerated Energy Innovations and Emerging Technologies

Intelligent Battery Health-Aware Energy Management Strategy for Hybrid Electric Bus: A Deep Reinforcement Learning Method Ruchen Huang, Hongwen He

Abstract

This paper proposes an intelligent battery health-aware energy management strategy (EMS) for the hybrid electric bus (HEB) with a deep reinforcement learning (DRL) method. Firstly, an EMS based on twin delayed deep deterministic policy gradient (TD3) algorithm considering battery health is innovatively designed to minimize the total operating cost of the HEB. Secondly, the superiority of the proposed EMS over the state-of-the-art deep deterministic policy gradient (DDPG) based strategy is validated. Simulation results show that the proposed EMS accelerates the convergence by 24.00% and reduces the total operating cost by 9.58% compared with the EMS based on DDPG.

Keywords hybrid electric bus, energy management, battery health, deep reinforcement learning, twin delayed deep deterministic policy gradient (TD3)