This paper designs a performance analysis framework for electric vehicle taxis, aiming at promoting their wide deployment. Consisting of an event tracker, a stream handler, object interfaces, and strategy integrator, the analysis procedure can measure the performance of a dispatch and relocation strategy in terms of dispatch latency, customer waiting time, and the number of daily fast charging operations. Each pick-up and drop-off record from the actual call taxi system is associated with the corresponding taxi and charger object. It can host a new dispatch strategy to test and revise, while a specific road network and a future demand prediction model can be incorporated for better accuracy. This framework finds out that most battery charging can be done using slow chargers through the out-of-service intervals under the control of an intelligent coordinator for the fleet of member taxis, avoiding the significant increase in power load brought by fast charging operations. © 2014 Springer International Publishing Switzerland.
CITATION STYLE
Lee, J., Park, C. J., & Park, G. L. (2014). Design of a performance analyzer for electric vehicle taxi systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8398 LNAI, pp. 237–244). Springer Verlag. https://doi.org/10.1007/978-3-319-05458-2_25
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