This paper introduces an optimal sizing method for a catenary-free tram, in which both on-board energy storage systems and charging infrastructures are considered. To quantitatively analyze the trade-off between available charging time and economic operation, a daily cost function containing a whole life-time cost of energy storage and an expense of energy supplies is formulated for the optimal sizing problem. A mixed particle swarm optimization algorithm is utilized to find optimal solutions for three schemes: (1) ultracapacitors storage systems with fast-charging at each station; (2) battery storage systems with slow-charging at starting and final stations; (3) battery storage systems with fast-swapping at swapping station. A case study on an existing catenary-free tramline in China is applied to verify the effectiveness of the proposed method. Results show that a daily-cost reduction over 30% and a weight reduction over 40% can be achieved by scheme 2, and a cost saving of 34.23% and a weight reduction of 32.46% can be obtained by scheme 3.

As one of the most popular and important forms of massive transit, the public bus contributes to a healthier environment compared to private vehicles. Through the electrification of the public bus, energy consumption, carbon emission, and air pollution can be significantly reduced. However, the limited driving range and high battery replacement cost put significant barriers to its large-scale commercialization. Thanks to the development of wireless charging technology and opportunity charging strategy, the driving range can be improved. However, the battery has to suffer additional impulse current generated by opportunity wireless charging. In this paper, a hybrid energy storage system (HESS) that combines battery and supercapacitor and related energy control strategy is proposed to smoothen the impulse current and extend the battery lifespan. A comprehensive investigation of the combined impacts of the opportunity charging and HESS is carried out in terms of driving range extension and battery lifespan improvement. The detailed HESS model and powertrain model are built. A global optimizing method, dynamic programming, is adopted as the energy management strategy under the Chinese heavy-duty commercial vehicle test cycle-bus (CHTC-B). A battery degradation model is employed to evaluate its health with 60 kW wireless charging. The results demonstrate that the proposed energy control strategy for HESS could improve battery health and extend bus driving range concurrently via opportunity charging.