Cost-Benefit Analysis of Electric Bus Fleet with Various Operation Intervals

Abstract

Electric buses are particularly suitable for city and suburban routes due to zero local exhaust and noise emissions. The operation schedule interval defines the charging power, bus fleet size and total cost of ownership of a bus. We propose a novel cost-benefit method for the scheduling of an electric city bus fleet on a single route. Three different charging infrastructure scenarios were considered. In the first scenario, only one charging station was used. The second scenario considered two charging stations that were located at the same terminus. In the third scenario, two charging stations were located at opposite terminuses. The costs and utilization rates of the buses were analyzed with operation intervals up to 40 minutes. The first scenario with a single charging station had the lowest costs for the entire bus fleet system when the utilization rate was considered. Furthermore, the results show that certain schedule intervals are more cost-beneficial in terms of vehicle specific life-cycle costs than others. In the future, the proposed method is expanded to aid the design of bus network scheduling under energy demand uncertainty.

Energy Consumption Estimation of the Electric Bus Based on Grey Wolf Optimization Algorithm and Support Vector Machine Regression

“…Chen et al (2018) investigated the cost competitiveness of different types of charging infrastructure [14]. Jari et al (2018) considered three different charging infrastructure scenarios for a novel cost-benefit method for the scheduling of an electric city bus fleet on a single route [15]. Lajunen (2018) concluded that high energy capacity of the battery system was crucial for the overnight charging buses to achieve adequate daily operation, whereas the battery size had a minor impact on the energy consumption and lifecycle costs of the fast-charging buses [16].…”

A probabilistic fleet analysis for energy consumption, life cycle cost and greenhouse gas emissions modelling of bus technologies

“…End station charging of BEBs results in the lowest TCO of charging methods and may lead to lower TCO than diesel buses over the 12-year life. Fleet cost-effectiveness has been shown to vary with charging station placement and service frequency, but overall, larger fleets required at low service intervals increase TCO more aggressively than increasing battery capacity for additional range [26].…”

“…The model is not intended to fully optimize the number of vehicles or supportive charging infrastructure, requiring data intensive and computationally expensive models [10,24,65,66], but to simulate basic fleet operation with minimal inputs that can be obtained from existing departure schedules. Based on calculations by Lajunen [11] and Vepsäläinen et al [26], the model assumes each fleet must complete a set number of peak and off-peak operational cycles (drive cycle time plus waiting time at end station), determined by the service frequency. A rotating dispatch schedule is assumed so equal peak and off-peak cycles are covered over the life cycle.…”

Comparative TCO Analysis of Battery Electric and Hydrogen Fuel Cell Buses for Public Transport System in Small to Midsize Cities

“…There are only a few research studies that show a total cost of ownership (TCO) analysis of alternative power train technologies for specific cities [1,15,[18][19][20][21][22][23]. In each case study, several scenarios specialized in the cities were presented, with each presenting various research focuses.…”