Comparative Study of Equivalent Factor Adjustment Algorithm for Equivalent Consumption Minimization Strategy for HEVs
| Autor: | Fengqi Zhang, Kanghui Xu, Reza Langari, Lin Li |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Iterative method
Proportional control 020302 automobile design & engineering 02 engineering and technology 021001 nanoscience & nanotechnology State of charge 0203 mechanical engineering Robustness (computer science) Electronic countermeasure Torque Minification 0210 nano-technology Algorithm Driving cycle Mathematics |
| Zdroj: | 2018 IEEE Vehicle Power and Propulsion Conference (VPPC). |
| DOI: | 10.1109/vppc.2018.8604986 |
| Popis: | 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 evaluate the performance of the adaptation law from different aspects. The results show that the performance of EF adjustment algorithm not only relates to the State of Charge (SoC) deviation, 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. |
| Databáze: | OpenAIRE |
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