Comparative Study of Equivalent Factor Adjustment Algorithm for Equivalent Consumption Minimization Strategy for HEVs**Research supported by Shaanxi Provincial Department of Education. Conference Paper uri icon

abstract

  • © 2018 IEEE The performance of equivalent consumption minimization strategy (ECMS) is strongly dependent on the choice of equivalent factor (EF). This paper provides a comparative study for EF adjustment algorithm for hybrid electric vehicles. The aim is to illustrate the robustness of each controller and evaluate their pros and cons. To obtain a fair comparison, a new evaluation index is introduced. Four controllers are developed to determine the EF. Iterative Method (IM) is used as a benchmark to obtain the optimal EF. Simulations for three driving cycles using ECMS are conducted to illustrate the performance of the adaptation law from different aspects. The results show that the performance of EF adjustment algorithm not only relates to the initial EF, but also dependent on the driving cycle. The PI adaptation law and Discrete controller (DC) with a lower computational burden achieve better charge-sustainability while the P controller performs worse when the variation of initial EF exists.

author list (cited authors)

  • Zhang, F., Xu, K., Li, L., & Langari, R.

citation count

  • 5

publication date

  • August 2018

publisher