Reducing fuel consumption and related emissions through optimal sizing of energy storage systems for diesel-electric trains.

• Optimal Lithium-ion battery sizing for hybrid diesel-electric train is presented. • Bi-level optimization approach integrates optimal sizing and control levels. • Two energy management strategies are developed and compared. • Trade-off between fuel savings and hybridization cost is analyzed. • Fuel savings and CO 2 emissions reduction of up to 34.5% is obtained. Hybridization of diesel multiple unit railway vehicles is an effective approach to reduce fuel consumption and related emissions in regional non-electrified networks. This paper is part of a bigger project realized in collaboration with Arriva, the largest regional railway undertaking in the Netherlands, to identify optimal solutions in improving trains' energy and environmental performance. A significant problem in vehicle hybridization is determining the optimal size for the energy storage system, while incorporating an energy management strategy as well as technical and operational requirements. With the primary requirement imposed by the railway undertaking to achieve emission-free and noise-free operation within railway stations, we formalize this as a bi-level multi-objective optimization problem, including vehicle performance, the trade-off between fuel savings and hybridization cost, influence of the energy management strategy, and other constraints. By deriving a Li-ion battery parameters at the cell level, a nested coordination framework is employed, where a brute force search finds the optimal battery size using dynamic programming for full controller optimization for each feasible solution. In this way, the global minimum for fuel consumption for each battery configuration is achieved. The results from a Dutch case study demonstrated fuel savings and CO 2 emission reduction of more than 34% compared to a standard vehicle. Additionally, benefits in terms of local pollutants (NO x and PM) emissions are observed. Using an alternative sub-optimal rule-based control demonstrated a significant impact of the energy management on the results, reflected in higher fuel consumption and increased battery size together with corresponding costs. [ABSTRACT FROM AUTHOR]