Simulation Of Energy Control Strategy For Parallel Hybrid Electrical Vehicles

If the structure and the characteristic of hybrid electric vehicle’s (HEV’s)components are given, the HEV’s fuel economy and emission level are largelydetermined by HEV control strategy. The research in the field of HEV’s fuelconsumption, emission and battery state of charge (SOC) is far from finished. So thescope of this study is mainly focused on reducing the HEV’s fuel consumption and gasemission:①The mathamtic modles of HEV drivetrain’s components are the foundation offurther research on HEV control strategy. First, the structure and bench-test of theHEV’s components are analyzed. Then, based on the ADVISOR which is developedby National Renewable Energy Laboratory (NREL) in United States, the simulationmodels of HEV system and its components are established. Because the quasi-staticmodels are widely applied in ADVISOR, the dynamic characteristics which is less than1sec of HEV system in this paper will be ignored.②Although the rule based control strategy (RBCS) has some advantages includingsimple structure, pellucid parameters, easy to build, a large number of trail-errorexperiments are need to obtain a set of feasible thresholds with less robustness andRBCS cannot achieve optimal performance under different driving cycle. In order tosolve this problem, the operation modes of RBCS under different driving condition areanalyzed to find out the drawbacks within it. Then, the fuzzy logic reasoning is appliedto obtain a fuzzy logic control strategy (FLCS) which can easily adapt to differentdriving cycles.③Comparing to RBCS, although FLCS get some considerable improvement infuel economy, the emission is not treated as a independent optimal object in both FLCSand RBCS. Actually, in FLCS, it is supposed that the emssion will be reduced alongwith the reduction of fuel consumption. Because the engine’s low fuel consumptionzone is not inconsistent with its low emission zone, FLCS obviously cannot guaranteethe performance of HEV’s emission reduction. Thus, based on FLCS, a minimumweighted membership deviation control strategy (MDCS) is established. In MDCS, theconcept of motor’s equivalent energy consumption is applied to make sure the fuelconsumption and emission are all treated as objectives of the optimal problem which issolved by the minimum weighted membership deviation algorithm. ④Because, under different driving condition, the supervisory controller getsdifferent preference among optimal objectives. For example, the emission reduction ismore important than fuel economy in urban driving condition while the opposite is truein rural driving condition. Since MDCS lacks the flexibility to adapt to different drivingcondition, a varying-domain control strategy (VDCS) is proposed to solve this problem.In VDCS, the motor’s equivalent energy consumption is also applied to obtain theHEV’s overall energy consumption. And the non-strict constrained priorities amongobjectives are introduced with the varying-domain optimal algorithm. At last, theoptimal problem is solved by a genetic algorithm, namely, GENOCOPIII.In this study, HEV control strategy is theory analyzed and simulated. And thesimulation restults are consistent with theory analysis. In conclusion, this study not onlylays a theoretical foundation for future research but also provides a feasible provingmethod.