Towards an Energy Efficient Solution for Bike-Sharing Rebalancing Problems: A Battery Electric Vehicle Scenario

Abstract

A free-float bike-sharing system faces various operational challenges to maintain good service quality while optimizing the operational cost. The primary problems include the fulfillment of the users demand at all stations, and the replacement of faulty bikes presented in the system. This study focuses on a free-float bike-sharing system rebalancing problem (FFBP) with faulty bikes using battery electric vehicles (BEVs). The target inventory of bikes at each station is obtained while minimizing the total traveling time through the presented formulation. Using CPLEX solver, the model is demonstrated through numerical experiments considering the various vehicle and battery capacities, and a cost–benefit analysis is performed for BEV and conventional internal combustion engine vehicles (ICEVs) while taking the BEV manufacturing and indirect emission into account. The results show that the annual cost incurred on an ICEV is 56.9% more as compared to the cost of using an equivalent BEV. Since BEVs consume less energy than conventional ICEVs, the use of BEVs for rebalancing the bike-sharing systems results in significant energy savings for an urban transport network. Moreover, the life cycle emissions of an ICEV are 48.3% more as compared to an equivalent BEV. Furthermore, the operational cost of a BEV significantly reduces with the increase in battery capacity.

External Environmental Analysis for Sustainable Bike-Sharing System Development

“…There are also three environmental factors clustered in this group: using renewable energy sources for charging public bike stations (E3), smartphone chargers in public bikes (E4), and low emission of harmful substances (E5). A similar analysis of renewable energy usage in BSSs was presented by Usama et al [99], Jia et al [100], Matias et al [101], carbon dioxide emissions by Chen et al [102], and Kou et al [103]. There are also two technological factors in this group: the extension and modernization of bicycle city routes (T2) and improvement of their markings (T5), which are naturally connected, and change as the network of bikesharing connections between the cities of the conurbation in the southern part of Poland grow.…”

Implications of the Relocation Type and Frequency for Shared Autonomous Bike Service: Comparison between the Inner and Complete City Scenarios for Magdeburg as a Case Study

“…This way, the bike rebalancing operation becomes more sustainable, with no gas emissions and less congestion compared to conventional systems. The assessment of OSABS benefits and the evaluation of rebalancing strategy need to be assessed by life cycle assessment (LCA) in future work [51,52] for a better comparison between OSABS and CBS.…”

The Biobjective Bike-Sharing Rebalancing Problem with Balance Intervals: A Multistart Multiobjective Particle Swarm Optimization Algorithm

“…Broken bikes are considered by Wang and Szeto [22] with the objective of minimizing the total CO 2 emissions of all vehicles. Usama et al [23] also consider replacing faulty bikes in the system with the following objectives: user dissatisfaction to unmet demand, vehicle routing costs including handling, loading, unloading, and traveling cost, and the waiting time of repositioning vehicles.…”