摘要
本研究对串联式和并联式混合动力汽车的控制策略进行了分析。在CYC NEDC和CYC HWFET循环工况下,通过仿真分析比较了分别采用电力辅助控制、自适应控制、遗传实时控制3种不同控制策略的车辆性能。结论表明,采用遗传实时控制策略可以有效提高汽车的燃油经济性、排放性能。在NEDC路况下行驶,遗传实时控制相对于辅助动力源控制,燃油经济性改善47.4%,HC排放降低6.2%,CO排放降低24.6%,NOx排放降低7.7%;遗传实时控制相对于自适应控制,燃油经济性改善20.4%,HC排放降低0.6%,CO排放降低29.5%,NOx排放降低13.5%。在HWFET路况下行驶也得到比较理想的结果。
Optimizing of Muti-Energy powertrain control strategy was the key technique of Hybrid Electric Vehicle. Three kinds of structures of HEV and their control strategy were analysed--Series Hybrid Electric Vehicle, Parallel Hybrid Electric Vehicle, and PSHEV. For driving cycles of CYC NEDC and CYC _ HWFET, three control strategies such as Electric Assistant Control, Adaptive Control Strategy and Genetic Algorithms Control were simulated to analyse vehicle performance. The results of simulation indicated that the fuel consumption efficiency and emission performance were improved by using Genetic Algorithms Control. In CYC _ NEDC, compared with Electric Assistant Control, fuel consumption efficiency was improved 47.4 %, HC decreased 6.2 %, CO decreased 4.6%, and NOx decreased 7.7%. Compared with Adaptive Control Strategy, fuel consumption efficiency was improved 20.4 % , HC decreased 0.6 %, CO decreased 29.5 %, and NOx decreased 13.5 %. In CYC HWFET, the same results were achieved.
出处
《河北农业大学学报》
CAS
CSCD
北大核心
2007年第4期93-96,共4页
Journal of Hebei Agricultural University
基金
河北农大非生命新兴学科基金资助项目
关键词
混合动力汽车
多能源动力总成
控制
遗传算法
仿真
hybrid electric vehicle
muti-energy powertrain
control
genetic algorithms
simulation
