Sustainable driving operations of urban plugin hybrid buses considering restricted emission mapping zones

Abstract

Road traffic is the major source of air and noise pollution. It is also one of the largest contributors to anthropogenic greenhouse gas emissions. Transport electrification can significantly reduce these negative externalities. However, electric buses do not often meet public transport requirements, due to their limited battery capacity. In contrast, plug-in hybrid electric buses offer a versatile alternative, providing zero-emission capabilities that depend on battery capacity, charging frequency, and the distribution of electric drive along a route. However, current electric drive assignment systems are oversimplified, thus not fully leveraging their potential. This work extends our previous research, which introduced a novel combinatorial optimization problem aimed at determining optimal electric drive assignment strategies for Plugin Electric Hybrid (PEH) buses. A large number of bus lines as well as zero-emission and restricted-emission zones are considered. The objectives are to maximize the buses’ electric range and minimize the overall pollution while adhering to mandatory zero-emission and restricted-emission zones. In this study, we analyze seventy bus lines from Barcelona’s urban public bus network (Spain), and tackled this large problem with two parallel implementations of the Cooperative Co-evolutionary Multi-objective Cellular Genetic Algorithm (CCMOCell). The strategies provided by both CCMOCell versions are validated against GreenK, a state of the art heuristic that only focuses on the electric range. Results demonstrate that the obtained solutions achieve up to 7.67% reduction in carbon dioxide (CO) emissions, compared to GreenK, at the cost of a slight decrease in terms of electric range, i.e. 2.28%. However, the strategy found by GreenK is unfeasible, because it exceeds the pollution threshold established for one restricted-emission zone by 635 COkilograms per day.