Deep Deterministic Policy Gradient-DRL Enabled Multiphysics-Constrained Fast Charging of Lithium-Ion Battery

Fast charging is an enabling technique for the large-scale penetration of electric vehicles. This article proposes a knowledge-based, multiphysics-constrained fast strategy lithium-ion battery (LIB), with consciousness thermal safety and degradation. A universal algorithmic framework combining model-based state observer deep reinforcement learning (DRL)-based optimizer proposed, first time, to provide LIB solution. Within DRL framework, multiobjective optimization problem formulated by penalizing over-temperature An improved environmental perceptive deterministic policy gradient (DDPG) algorithm priority experience replay exploited tradeoff smartly rapidity compliance physical constraints. The proposed DDPG-DRL compared experimentally rule-based strategies state-of-the-art model predictive controller validate its superiority in terms rapidity, enforcement life extension, as well computational tractability.