中南大学学报（自然科学版）2012，Vol.43Issue(11)：4306-4312,7.
并联式混合动力逻辑门限控制参数智能优化
Intelligent optimization for logic threshold control parameter on parallel hybrid electric vehicle
摘要
Abstract
In order to reduce the fuel consumption and emissions of the parallel hybrid electric vehicle, a new optimization model of the logic threshold control parameter was established based on adaptive chaos particle swarm algorithm. The model was verified by comparing the optimized results of ACPSO algorithm with PSO and those of GA algorithm. Based on ADVISOR, the optimized fuel consumption and emissions were compared with those which were not optimized. The results show that the ACPSO not only has great advantages of convergence property, but also avoids being trapped in local optimum. There is at least 12% reduction in the fuel consumption per 100 km and 6%, 5% and 8% decrease in the discharge of HC, CO and NOX respectively in UDDC working conditions.关键词
自适应混沌粒子群优化算法/混合动力/智能优化/仿真Key words
adaptive chaos particle swarm optimization/ hybrid electric vehide/ intelligent optimization/ simulation分类
能源科技引用本文复制引用
申爱玲,袁文华,左青松,伏军..并联式混合动力逻辑门限控制参数智能优化[J].中南大学学报（自然科学版）,2012,43(11):4306-4312,7.基金项目
湖南省自然科学基金资助项目(09JJ6077) （09JJ6077）
