Abstract
This paper focuses on the parameter optimization for the CVT (a continuously variable transmission) based plug-in 4WD (4-wheel drive) hybrid electric vehicle powertrain. First, the plug-in 4WD hybrid electric vehicle (plug-in 4WD HEV)’s energy management strategy based on the CD (charge depleting) and CS (charge sustain) mode is developed. Then, the multi-objective optimization’s mathematical model, which aims at minimizing the electric energy consumption under the CD stage, the fuel consumption under the CS stage and the acceleration time from 0–120 km/h, is established. Finally, the multi-objective parameter optimization problem is solved using an evolutionary based non-dominated sorting genetic algorithms-II (NSGA-II) approach. Some of the results are compared with the original scheme and the classical weight approach. Compared with the original scheme, the best compromise solution (i.e., electric energy consumption, fuel consumption and acceleration time) obtained using the NSGA-II approach are reduced by 1.21%, 6.18% and 5.49%, respectively. Compared with the weight approach, the Pareto optimal solutions obtained using NSGA-II approach are better distributed over the entire Pareto optimal front, as well as the best compromise solution is also better.
Highlights
Owing to regulations on fuel economy and emissions become more and more stringent, the development of electrified vehicles in recent years have been a surging trend [1,2]
The powertrain’s dynamic model, energy management strategy and calculation model of the objective function were built by using MATLAB/Simulink simulation software, in which the driving objective function were built by using MATLAB/Simulink simulation software, in which the driving cycles were selected under the urban road environment, as shown in Figure 11, the CD stage ran under cycles were selected under the urban road environment, as shown in Figure 11, the CD stage ran one FUDS driving cycle and the charge sustain sustain (CS) stage ran under three repetitive under one FUDS driving cycle and the CS stage ran under three
According to this table, compared with the original scheme (OS), the final optimized scheme (NDS-2)’s 100 km electric energy consumption, 100 km fuel consumption and acceleration time were reduced by 1.21%, 6.18% and 5.49%, respectively
Summary
Owing to regulations on fuel economy and emissions become more and more stringent, the development of electrified vehicles in recent years have been a surging trend [1,2]. The rule control strategy based on the charge depleting–charge sustain (CD–CS) mode does not need to know the driving cycles beforehand, and the calculation is small, so it is widely used in the real vehicle control of PHEVs. As a summary of the entire literature review, in order to complete the plug-in 4WD HEV’s parameter optimization well, the simultaneous optimization for the main parameters of powertrain and control strategy is necessary, multi-objective optimization should be taken into account and the rule control strategy based on the CD–CS mode for plug-in 4WD HEVs should be developed.
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