Synergistic Multi-Agent Reinforcement Learning for Energy Management in Fuel Cell Vehicles with Integrated Temperature Control
The coupled effects of power distribution and stack temperature strongly influence hydrogen economy, durability, and operating stability in proton exchange membrane fuel cell (PEMFC) vehicles. This study proposes an integrated energy–thermal management strategy based on the multi-agent deep deterministic policy gradien...