Driving-style-aware energy management strategy for FCHEV based on ECMS

To improve energy economy of fuel cell hybrid electric vehicle (FCHEV), it is of great significance to research driving style recognition based on equivalent consumption minimization strategy (ECMS). For driving style recognition problem, the principal component analysis (PCA) method is adopted to select the speed and the absolute values of acceleration as driving style identification parameters and the fuzzy-logic controller optimized by genetic algorithm (GA) is designed to identify driving style.

Afterwards, the driving style optimal control strategy is realized by matching the recognized driving style with the optimal equivalent factor in each driving condition and the matched equivalent factor is combined with the objective function of ECMS. The effectiveness of proposed driving style based on ECMS is validated by real vehicle test, which indicates that, compared with the strategy without considering driving styles, the proposed driving style recognition based ECMS reduces the hydrogen consumption of FCHEV by 3.7% in the combination of HWFET and UDDS.