Abstract:

The vehicle mass variation during the operation of buses affects power demand of the vehicle, which can result in poor performance of energy management strategies. To this end, a hybrid electric bus energy management strategy based on proximal policy optimization-adaptive simulated annealing (PPO-ASA) is proposed. ASA is introduced into PPO to perturb policy parameters according to policy entropy before the policy update, and the perturbed policies are adaptively accepted or rejected by employing the Metropolis criterion, thus improving the exploration capability of the policy and convergence stability. Experimental results show that the proposed method outperforms the charge depleting-charge sustaining (CD-CS) control strategy when considering vehicle mass variation, achieving a 5.8% reduction in fuel consumption per 100 km and demonstrating better adaptability to driving cycles than other algorithms. The energy management strategy considering vehicle mass variation has the lowest cumulative fuel consumption, reducing fuel consumption by 4.5% compared to the strategy designed under the empty load.

Key words: energy management strategy, PPO algorithm, ASA, LSTM model, CD-CS control strategy, vehicle mass variation