Multi-performance enhanced eco-driving strategy for connected fuel cell hybrid electric bus based on stein soft actor-3-critic

Abstract

Eco-driving strategies increasingly emphasize enhancing multi-performance including safety, comfort, durability, and traffic efficiency under optimal energy-saving. This paper introduces a multi-performance enhanced eco-driving strategy for connected fuel cell hybrid electric buses (FCHEBs) based on the stein soft actor-3-critic (SSA3C) algorithm. By leveraging the correlation between the international roughness index (IRI) and weighted root mean square acceleration (WRMSA), energy management system (EMS) and adaptive cruise control (ACC) are integrated the to enhancing multi-performance including vertical comfort and energy efficiency. To address the insufficient action representation and overestimation of Q-values of traditional soft actor-critic (SAC) algorithm, improvements are made to the actor and critic networks using stein variational gradient descent (SVGD) and clipped triple Q-learning (3C), respectively. Composite cycles integrating the standard cycle and IRI are developed to enhance the strategy's generalization. Experimental results indicate that the proposed eco-driving strategy, while maintaining dynamics, safety, durability, and efficiency, efficiently achieves 98.1 % energy savings and equivalent comfort level as dynamic programming (DP). Ablation experiments on vertical comfort demonstrate improvements of 1.24 % in energy efficiency and 2.94 % in WRMSA. Finally, the effectiveness of the network improvements and the adaptability of the proposed strategy are demonstrated through comparative experiments.