Abstract:

A synthetic parameter optimization method of hybrid electric vehicle (HEV) was proposed to solve
the problem that energy management and matching of power system are usually conducted respectively.
Considering the cost of electric drive system and using an improved fuzzy energy management strategy, the
parameters of energy management strategy and the parameters of power system were taken as decision
variables; meanwhile the equivalent synthetic fuel consumption and the cost of motor and battery pack were
taken as objective functions. Then under the simulation environment of ADVISOR, a multi-objective genetic
algorithm was used to find the optimal solution. Simulation results show that under the constrains of vehicle
dynamic quality, the equal fuel consumption per 100km is reduced by 23.0%, the cost of motor and battery pack
is reduced by 41.9%, the CO emissions per kilometer is reduced by 10.8%, the HC emissions per kilometer is
reduced by 22.2%, the NOx emissions per kilometer is reduced by 27.0%, as well as the efficiency of engine and
motor has been improved. These results verify the effectiveness of the method.

Key words: hybrid electric vehicle, cost model, synthetic parameter optimization, fuzzy energy management strategy, multi-objective genetic algorithm