Battery Thermal- and Health-Constrained Energy Management for Hybrid Electric Bus based on Soft Actor-Critic DRL Algorithm
Jingda Wu, Zhongbao Wei, Weihan Li, Yu Wang, Yunwei Li, Dirk Uwe Sauer, IEEE Transactions on Industrial Informatics, August 2020. doi: 10.1109/TII.2020.3014599
Energy management is critical to reduce the size and operating cost of hybrid energy systems, so as to expedite on-the-move electric energy technologies. This paper proposes a novel knowledge-based, multi-physics-constrained energy management strategy for hybrid electric bus (HEB), with an emphasized consciousness of both thermal safety and degradation of onboard lithium-ion battery (LIB) system. Particularly, a multi-constrained least costly formulation is proposed by augmenting the over-temperature penalty and multi-stress-driven degradation cost of LIB into the existing indicators. Further, a soft actor-critic deep reinforcement learning strategy is innovatively exploited to make an intelligent balance over conflicting objectives and virtually optimize the power allocation with accelerated iterative convergence. The proposed strategy is tested under different road missions to validate its superiority over existing methods in terms of the converging effort, as well as the enforcement of LIB thermal safety and the reduction of overall driving cost.