Energy Management of Hybrid Electric Urban Bus by Off-Line Dynamic Programming Optimization and One-Step Look-Ahead Rollout

Due to the growing air quality concern in urban areas and rising fuel prices, bus fleets are progressively turning hybrid electric vehicles (HEVs) which show higher efficiency lower emissions comparison with conventional vehicles. HEVs can reduce consumption by combining different energy sources (i.e., batteries). In this sense, performance of is strongly dependent on management strategy (EMS) coordinates available exploit their potential. While most EMSs calibrated for general driving conditions, paper proposes adapt EMS specific conditions a particular route. The proposed algorithm relies fact that partial information cycle be assumed since, case bus, considered route periodically covered. According hypothesis, presented based estimating from previous trip This initial used compute theoretical optimal solution dynamic programming. obtained control policy (particularly cost-to-go matrix) stored subsequent cycles applying one-step look-ahead roll out, then, adapting actual but exploiting similarities same To justify strategy, discusses common patterns route, pointing out several metrics how single captures key parameters optimization. Then, (off-line programming optimization rollout) described. Results simulation method able keep battery charge within required range achieve near-optimal performance, only 1.9% increase regards optimum. As reference comparison, equivalent minimization (ECMS), widespread HEV management, produces an respect 11%.