LAUSR

Besides fuel economy, gear shifting and engine start-stop frequency in the optimal energy management for hybrid electric vehicles (HEVs) will also influence the overall performance and drivability. However, such drivability concerns will also impact the vehicle’s energy efficiency. To solve this conflicting optimization problem, this paper aims to find the proper weighing of the conflicting costs to achieve a right balance based on sensitivity analysis. The problem is formulated by expanding the conventional cost function with additional penalty items for gear shifting and engine start-stop, and a range extended hybrid delivery truck is modeled as a case study. Dynamic programming (DP) algorithm is applied to guarantee all the comparisons are under the same benchmark, and a split-DP solution is carried out to accelerate the searching process. Analytical fitting and trend analysis methods are used to find the proper penalty factors. Eventually, a comprehensive comparison among optimized, experiential and none penalty factors is shown, indicating that such appropriate weighing can significantly improve drivability with only 0.2% more fuel cost.