Optimisation of energy flow management in hybrid electric vehicles via genetic algorithms

被引:0
|
作者
Piccolo, A [1 ]
Ippolito, L [1 ]
Galdi, VZ [1 ]
Vaccaro, A [1 ]
机构
[1] Univ Salerno, Dept Elect & Elect Engn, I-84084 Fisciano, Italy
关键词
hybrid helectric vehicles; hybrid powertrain; power flow management; genetic algorithms; genetic optimisation;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Hybrid electric vehicles powertrain, combining electric motor with an auxiliary power unit, can offer a sensible improvement of the overall vehicle environmental impact achieving at the same time a rational energy employment. This valuable features can be magnified designing a suitable energy flow management unit whose main task is to split the instantaneous vehicle power demand between the internal combustion engine and the electric motor ensuring that the power sources are operated at high efficiency operating points and the related vehicle emissions are minimised. In the present paper after a preliminary analysis on the strategy adopted an original methodology for the tuning of the characteristic parameters is presented. The proposed methodology, starting from the desired vehicle on road performance, identifies through the employment of a Genetic Algorithm the value of the energy flows management parameters that minimize a cost function descriptive of the design objectives in terms of fuel consumption and emissions. Some interesting simulation results will be discussed to prove the validity of the methodology, which will contribute to a substantial reduction of the pollutant emissions from hybrid electric vehicles.
引用
收藏
页码:434 / 439
页数:2
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