| The economic performanc and emissions performance of parallel plug-in hybridelectric vehicle (PHEV) has a close relationship with the accuracy of its energymanagement strategy (EMS), so that it’s an important task to fulfil in the PHEV field.Logic threshold EMS and fuzzy EMS are two kinds of practical EMS, but their rulesare based on experts’ experience which can not achieve optimum control, and theyneed optimizing with proper optimization algorithm.Therefore the optimization of these two kinds of EMS of parallel PHEV based onimproved chaos genetic algorithm is studied in this paper, which is based on the “985engineering” project of Hunan university and Key laboratory open fund project ofJiangsu province. And the main innovations and research work are expressed asfollows:(1) With the study on genetic algorithm (GA) and the mechanism of its defects,an improved (CGA) is proposed on baisis of convential CGA. The convergenceproperty of these three optimization algorithms is tested with three typical functions,and the result shows that the speed, stablity and quality of convergence of improvedCGA are greatly enhanced.(2) The conclusion that conventional single-mode logic threshold EMS is notsuitable for PHEV running in moderate distance suburb road and long distancehighway is proved by simulation. A double-mode logic threshold EMS according torode condition and distance is proposed. The control parameters of the strategy areoptimized with the improved CGA. The simulation result shows that, compared withthe prototype vehicle, the optimized double-mode logic threshold EMS can reduece thetransportation cost by10%on high way and21.3%on suburb road, meanwhile, theEMS have excellent emissions performance.(3) Fuzzy EMS is studied, and its membership functions and control rules areoptimized with the improved CGA to match parallel PHEV. The simulation resultshows the optimized fuzzy EMS can reduce the Fuel Consumption by5.15%andreduce CO emission by6.39%. |
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